U.S. patent number 11,226,299 [Application Number 16/947,276] was granted by the patent office on 2022-01-18 for systems and methods for determining at least one property of a material.
This patent grant is currently assigned to Nevada Nanotech Systems Inc.. The grantee listed for this patent is Nevada Nanotech Systems Inc.. Invention is credited to Jesse D. Adams, Christopher J. Dudley, Vaughn N. Hartung, Benjamin S. Rogers, Ralph G. Whitten, Alexander C. Woods.
United States Patent |
11,226,299 |
Rogers , et al. |
January 18, 2022 |
Systems and methods for determining at least one property of a
material
Abstract
A system for determining one or more properties of one or more
gases. The system comprises sensors configured to measure thermal
conductivity and exothermic responses of a sample at multiple
temperatures. Sensor responses to exposure to a gas sample at two
or more temperatures are compensated and analyzed by a subsystem.
The subsystem is configured to determine a thermal conductivity of
the gas sample at each of the two or more temperatures and
determine at least one component of the gas sample based at least
in part on the thermal conductivity value of the sample at each of
the two or more temperatures. Related systems and methods of
determining one or more properties of a sample are also
disclosed.
Inventors: |
Rogers; Benjamin S. (Reno,
NV), Dudley; Christopher J. (Reno, NV), Adams; Jesse
D. (Reno, NV), Whitten; Ralph G. (Reno, NV), Woods;
Alexander C. (Reno, NV), Hartung; Vaughn N. (Reno,
NV) |
Applicant: |
Name |
City |
State |
Country |
Type |
Nevada Nanotech Systems Inc. |
Sparks |
NV |
US |
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Assignee: |
Nevada Nanotech Systems Inc.
(Sparks, NV)
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Family
ID: |
1000006060200 |
Appl.
No.: |
16/947,276 |
Filed: |
July 27, 2020 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20200363358 A1 |
Nov 19, 2020 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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15674305 |
Aug 10, 2017 |
10724976 |
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62376675 |
Aug 18, 2016 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N
29/022 (20130101); G01N 29/036 (20130101); G01N
25/18 (20130101); G01N 27/18 (20130101); G01N
27/12 (20130101); G01N 29/326 (20130101); G01N
11/16 (20130101); G01N 27/16 (20130101); G01N
29/12 (20130101); G01N 2291/0427 (20130101) |
Current International
Class: |
G01N
25/18 (20060101); G01N 11/16 (20060101); G01N
29/32 (20060101); G01N 27/18 (20060101); G01N
29/02 (20060101); G01N 29/036 (20060101); G01N
27/12 (20060101); G01N 27/16 (20060101); G01N
29/12 (20060101) |
References Cited
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Other References
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|
Primary Examiner: Woodward; Nathaniel T
Assistant Examiner: Cotey; Philip L
Attorney, Agent or Firm: TraskBritt
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATION
This application is a divisional of U.S. patent application Ser.
No. 15/674,305, filed Aug. 10, 2017, now U.S. Pat. No. 10,724,976,
issued Jul. 28, 2020, which application claims the benefit under 35
U.S.C. .sctn. 119(e) of U.S. Provisional Patent Application Ser.
No. 62/376,675, filed Aug. 18, 2016, the disclosure of each of
which is hereby incorporated herein in its entirety by this
reference.
Claims
What is claimed is:
1. A system for determining at least one property of a sample, the
system comprising: at least one thermal conductivity sensor; at
least one damping sensor; and a subsystem configured to: while the
at least one thermal conductivity sensor is at a temperature
greater than 50.degree. C., determine a response of the at least
one thermal conductivity sensor to exposure to a sample; determine
a first difference comprising a difference between the response of
the at least one thermal conductivity sensor to exposure to the
sample and a baseline thermal conductivity response of the at least
one thermal conductivity sensor; determine a response of the at
least one damping sensor to exposure to the sample; determine a
second difference comprising a difference between the response of
the at least one damping sensor to exposure to the sample and a
baseline response of the at least one damping sensor; and determine
a presence of at least one component of the sample based, at least
in part, on a ratio of the first difference to the second
difference.
2. The system of claim 1, wherein: the baseline response of the at
least one thermal conductivity sensor comprises the response of the
at least one thermal conductivity sensor to exposure to air; and
the baseline response of the at least one damping sensor comprises
the response of the at least one damping sensor to exposure to
air.
3. The system of claim 1, wherein the subsystem is configured to
determine a concentration of the sample based on a magnitude of a
vector of the change in the thermal conductivity versus the change
in at least one resonant parameter.
4. The system of claim 1, wherein the subsystem is configured to
determine a presence of the at least one component of the sample
based on the ratio and a change in at least one of quality factor,
series resistance, bandwidth, inductance, or parallel capacitance
of the at least one damping sensor.
5. The system of claim 1, wherein the at least one damping sensor
comprises a microcantilever.
6. The system of claim 1, further comprising a controller
configured to ramp a temperature of the at least one thermal
conductivity sensor to a predetermined temperature while the at
least one thermal conductivity sensor is exposed to the sample.
7. The system of claim 1, further comprising at least one
environmental sensor configured to measure at least one of a
temperature, a pressure, a humidity, and a flowrate, wherein the
subsystem is further configured to compensate an output of the
thermal conductivity sensor and an output of the at least one
damping sensor for the at least one of temperature, pressure,
humidity, and flowrate.
8. The system of claim 1, further comprising a catalytic sensor,
wherein the subsystem is further configured receive an output from
the catalytic sensor responsive to exposing the catalytic sensor to
the sample and further configured to determine the presence of the
at least one component based on the output of the catalytic
sensor.
9. The system of claim 8, wherein the catalytic sensor comprises
one of a catalytic microhotplate sensor and a catalytic
microcantilever sensor.
10. The system of claim 8, wherein the subsystem is configured to
determine at least one of an identity and a concentration of at
least one component of the sample based, at least in part, on a
relationship between the response of the at least one thermal
conductivity sensor to exposure to the sample and the response of
the at least one damping sensor to exposure to the sample
responsive to detecting an exothermic response from the catalytic
sensor.
11. The system of claim 1, further comprising a metal oxide
semiconductor sensor configured to interact with one or more
specific analytes present in the sample, wherein the subsystem is
further configured to determine the presence of the at least one
component of the sample based on a response of the metal oxide
semiconductor sensor to exposure to the sample.
12. The system of claim 1, further comprising a microcantilever
sensor comprising a coating formulated to interact with one or more
specific analytes present in the sample, wherein the subsystem is
further configured to determine the presence of the at least one
component of the sample based on one or more resonant parameters of
the microcantilever sensor responsive to exposure to the
sample.
13. The system of claim 1, wherein the subsystem is further
configured to determine the first difference comprising a
difference between the response of the at least one thermal
conductivity sensor to exposure to the sample at the temperature
greater than 50.degree. C. and a response of the at least one
thermal conductivity sensor to exposure to the sample at an
additional, different temperature.
14. The system of claim 1, wherein the subsystem is further
configured to determine the presence of the at least one component
based on a ratio between a change in at least one resonant
parameter of the at least one damping sensor and a change in at
least one of quality factor, series resistance, bandwidth,
inductance, or parallel capacitance of the at least one damping
sensor.
15. A system for determining one or more properties of a sample,
the system comprising: a thermal conductivity sensor; a damping
sensor; and a subsystem configured to: determine a first difference
comprising a difference between a response of the thermal
conductivity sensor to exposure to a sample and a baseline response
of the thermal conductivity sensor; determine a second difference
comprising a difference between a response of the damping sensor to
exposure to the sample and a baseline response of the damping
sensor; and determine one or more properties of the sample based,
at least in part, on a ratio of the first difference to the second
difference.
16. The system of claim 15, wherein the subsystem is configured to
determine a concentration of an analyte in the sample.
17. The system of claim 15, wherein the subsystem is configured to
compensate for environmental effects based on a difference between
a response of the thermal conductivity sensor at a first
temperature and a response of the thermal conductivity sensor at a
second temperature.
18. The system of claim 15, further comprising a catalytic sensor,
the subsystem configured to determine the one or more properties of
the sample bases on a response of the catalytic sensor to exposure
to the sample.
19. The system of claim 15, wherein the subsystem is further
configured to determine the one or more properties of the sample
based on a change in one of a quality factor and a series
resistance of the damping sensor.
20. The system of claim 15, wherein the thermal conductivity sensor
comprises a microhotplate.
21. The system of claim 15, wherein the thermal conductivity sensor
comprises a microcantilever comprising a resistive heater.
22. A method of determining one or more properties of a sample, the
method comprising: measuring a response of a thermal conductivity
sensor to exposure to a sample; determining a first difference
comprising a difference between the response of the thermal
conductivity sensor to exposure to the sample and a baseline
response of the thermal conductivity sensor; measuring a response
of a damping sensor to exposure to the sample; determining a second
difference comprising a difference between the response of the
damping sensor to exposure to the sample and a baseline response of
the damping sensor; and determining one or more properties of the
sample based, at least in part, on the ratio of the first
difference to the second difference.
23. The method of claim 22, wherein determining one or more
properties of the sample based, at least in part, on a relationship
between the first difference and the second difference comprises
determining a concentration of an analyte in the sample based on
the second difference.
24. The method of claim 22, wherein measuring a response of a
thermal conductivity sensor to exposure to a sample comprises
measuring a first response of the thermal conductivity sensor to
exposure to the sample at a first temperature, further comprising:
measuring a second response of the thermal conductivity sensor to
exposure to the sample at a second temperature; and compensating
the response of the thermal conductivity sensor for environmental
factors based on the first response and the second response.
25. The method of claim 22, further comprising: measuring a
response of a catalytic sensor to exposure to the sample; and
determining the one or more properties of the sample based on the
response of the catalytic sensor to exposure to the sample.
Description
TECHNICAL FIELD
Embodiments of the disclosure relate to systems and sensors for the
detection, quantification, and/or identification of materials
(e.g., vapors, gases, etc.), and to related methods. More
particularly, embodiments of the disclosure relate to systems and
sensors for determining a presence of one or more components in a
sample, determining a concentration of one or more components of
the sample, determining an identity of the one or more components
in the sample, and determining one or more other properties of the
sample, and to related methods of sample analysis.
BACKGROUND
Catalytic sensors have been used to detect flammable gases in some
applications. However, catalytic sensors have several shortcomings
that limit their performance and accuracy. Disadvantages of
catalytic sensors include drift and deterioration due to ageing and
poisoning of the catalyst, which may affect a magnitude of response
therefrom and, therefore, an accuracy thereof.
Microcantilevers have been demonstrated as gas sensor devices,
usually with coatings that attract specific gases. When mass is
added to the cantilever, a shift in its resonant frequency can be
detected. The change in resonant frequency is proportional to the
mass change on the microcantilever. It is also known that an
uncoated microcantilever can be used to sense the viscosity and
density of a gas. Density and viscosity can be considered in
composite by simply observing the resonant frequency shift, which
may be proportional to viscous damping (VD), or density and
viscosity can be deconvoluted by considering both resonant
frequency and quality factor changes (Boskovic 2002).
Also known is the physical relationship between a thermal
conductivity (TC) and a density of a gas. This can be exploited to
identify certain gases (Groot 1977 & Loui LLNL 2014). However,
some gases have overlapping, or nearly overlapping, TC versus
density vectors, making it difficult to distinguish these gases
from each other. Such a technique is also unable to detect multiple
gases in a gas mixture since mixed gases may exhibit a thermal
conductivity different than the thermal conductivity of the
components of the mixture and can lead to erroneous or unreliable
measurement results.
Some gases have TC versus VD vectors that are very similar to air,
e.g., oxygen (O.sub.2), carbon monoxide (CO), and nitric oxide
(NO). Some gases, such as hydrogen sulfide (H.sub.2S), cannot be
detected at low enough concentrations using the TC versus VD vector
alone. Metal oxide semiconductor (MOS) and coated microcantilevers
frequently have gas cross sensitivities and may be unable to
distinguish between several different gases. As one example,
current sensors for flammable and other hazardous gases (e.g.,
catalytic bed sensors, nondispersive infrared (NDIR) sensors,
thermal conductivity sensors) are unable to determine a single
property of a given gas or gas mixture and are unable to
self-correct an output thereof to determine, for example, a
concentration of the gas. Accordingly, in some instances, such
sensors may not be able to distinguish between, for example, a
first gas having a concentration of 500 ppm and a second gas having
a concentration of, for example, 5,000 ppm.
For the foregoing reasons, there is a need for a system and method
that overcomes conventional sensor disadvantages and that can
reliably detect, identify, and/or quantify gases.
BRIEF SUMMARY
The present invention is directed to a system and method that can
reliably detect, identify, and/or quantify a sample (e.g., vapors,
gases, liquids, combinations thereof, etc.). In one embodiment, the
system includes a catalytic sensor, a thermal conductivity sensor,
a damping sensor, one or more microcantilever sensors comprising a
coating material, one or more metal oxide semiconductor (MOS)
sensors, one or more environmental sensors (e.g., temperature,
pressure, humidity (relative humidity, absolute humidity, or both),
and flowrate), and a processing subsystem with software for
interrogating, compensating, calibrating, analyzing, detecting
faults, and reporting the results, for example.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
FIG. 1 illustrates an overall block diagram of a system for
measuring gas properties, in accordance with embodiments of the
disclosure;
FIG. 2A illustrates a top view of a microhotplate of a detector, in
accordance with embodiments of the disclosure;
FIG. 2B illustrates a cutaway side view of FIG. 2A shown for
clarity and taken along section line B-B of FIG. 2A;
FIG. 3A is a graph illustrating a thermal conductivity of several
gases at two temperatures;
FIG. 3B is a graph illustrating a relationship between a ratio of
the thermal conductivity of several gases at a first temperature to
the thermal conductivity of the gases at a second temperature;
FIG. 3C is a graph illustrating a relationship between a ratio of
thermal conductivity at two temperatures to a ratio of thermal
conductivity to concentration for various gases;
FIG. 3D is a graph illustrating a relationship between a ratio of
the thermal conductivity of the sample at a first temperature to
the thermal conductivity of the gas at the second temperature and
an average molecular weight of the sample;
FIG. 4 is a simplified flow diagram of a method of determining one
or more properties of a sample, in accordance with embodiments of
the disclosure;
FIG. 5A is a plot of thermal conductivity versus temperature for
various gases;
FIG. 5B is a gas specific ramped response of thermal conductivity
versus temperature;
FIG. 6 is a simplified flow diagram of a method of determining one
or more properties of a sample, in accordance with embodiments of
the disclosure;
FIG. 7A is a top view of a microcantilever of a detector, in
accordance with embodiments of the disclosure;
FIG. 7B illustrates a cutaway side view of FIG. 7A shown for
clarity and taken along section line B-B of FIG. 7A;
FIG. 7C is a schematic of an equivalent circuit model (ECM) of a
microcantilever, in accordance with embodiments of the
disclosure;
FIG. 8A illustrates a plot of thermal conductivity versus viscous
damping for various gases;
FIG. 8B is a graph illustrating a series resistance and a resonant
frequency of a plurality of gases;
FIG. 8C is a graph illustrating a relationship between a change in
resonant frequency to a change in series resistance of a
microcantilever, in accordance with embodiments of the
disclosure;
FIG. 9A is a top view of a microhotplate with interdigitated
electrodes used for measuring electrical characteristics of a MOS
sensor, in accordance with embodiments of the disclosure;
FIG. 9B illustrates a cutaway side view of FIG. 9A shown for
clarity and taken along section line B-B of FIG. 9A;
FIG. 10 illustrates a summary overview of a typical system process
sequence, in accordance with embodiments of the disclosure;
FIG. 11 is a graph illustrating a relationship between a change in
quality factor of a microcantilever, a change in resonant frequency
of the microcantilever, and a change in thermal conductivity of a
sample, which may be used to determine one or more properties of a
sample, in accordance with embodiments of the disclosure;
FIG. 12A is a graph illustrating a relationship between several
parameters that may be obtained with individual sensors of a
detector, in accordance with embodiments of the disclosure;
FIG. 12B is a radar plot of sensor responses used to create a
fingerprint of the responses, in accordance with embodiments of the
disclosure;
FIG. 12C is a radar plot of sensor responses used to create a
"fingerprint" of the responses, in accordance with other
embodiments of the disclosure;
FIG. 12D illustrates how the radar plots can be analyzed in a time
sequence when gases are separated (such as by a gas chromatograph)
ahead of the gas sensors;
FIG. 13 is a simplified flow diagram illustrating a method of
determining one or more properties of a sample, in accordance with
embodiments of the disclosure;
FIG. 14 is a simplified flowchart of processing for detecting,
quantifying, and identifying a flammable gas, in accordance with
embodiments of the disclosure;
FIG. 15A is a simplified flowchart for an embodiment for
determining at least one property of a sample using a thermal
conductivity sensor;
FIG. 15B is a simplified flowchart for an alternate implementation
for detecting, quantifying, and identifying non-flammable gases, in
accordance with embodiments of the disclosure;
FIG. 16 is a flowchart for an embodiment of the disclosure; and
FIG. 17 is an overview of the individual system processes used in
some embodiments of the disclosure.
DETAILED DESCRIPTION
Illustrations presented herein are not meant to be actual views of
any particular material, component, or system, but are merely
idealized representations that are employed to describe embodiments
of the disclosure.
As used herein, the term "sample" means and includes a material
that may include one or more gases, one or more vapors, one more
liquids, and one or more solids for which at least one property is
to be determined. By way of nonlimiting example, a sample may
include a liquid and a gas in equilibrium.
As used herein, the terms "viscous damping" and "damping" may be
used interchangeably.
As used herein, the term "catalytic response" means and includes a
response (e.g., an output) of a catalytic sensor to exposure to a
sample. A catalytic response at a particular temperature means and
includes the response of a catalytic sensor to exposure to a sample
when the catalytic sensor is at the particular temperature.
As used herein, the term "catalytic activity" means and includes a
difference between a catalytic response of a catalytic sensor to
exposure to a sample while the catalytic sensor is at a particular
temperature and a baseline catalytic response of the catalytic
sensor when the catalytic sensor is at the particular
temperature.
As used herein, the term "vector" means and includes a quantity
having a direction (e.g., slope, angle, ratio, etc.) and a
magnitude based on two or more parameters (e.g., length, distance,
size, dimension, etc.). A vector may have a dimension in a
plurality of dimensions, such as two dimensions, three dimensions,
four dimensions, five dimensions, six dimensions, or more
dimensions. Two-dimensional vectors and three-dimensional vectors
may be visualized graphically when graphing one parameter against
one or two additional parameters. Although some vectors may be
visualized graphically, the disclosure is not so limited. A vector
may be multi-dimensional and contain three or more parameters. In
some instances, a multi-dimensional vector may be simplified by
defining each vector parameter as a ratio of two other parameters.
Accordingly, a vector may include a relationship between one
parameter with one or more additional parameters (e.g., a
relationship between a change in thermal conductivity as a function
of temperature, a relationship between a change in catalytic
activity as a function of temperature, a relationship between a
thermal conductivity and catalytic activity, etc.). In some
embodiments, such relationships may be expressed in terms of a
ratio.
According to embodiments described herein, a system, such as a
detector, may be configured to determine one or more properties of
a sample (e.g., a gas sample, a vapor sample, a liquid sample, or
combinations thereof). The one or more properties may include one
or more of a presence of one or more components (e.g., different
gas components) in the sample, an identity of the one or more
components in the sample, a concentration of the one or more
components in the sample, a molecular property of the sample (e.g.,
an average molecular weight of the sample), whether the sample
includes combustible gas and/or an explosive gas, a
catalytic-reaction onset (also referred to herein as a "light-off"
event) temperature of any combustible or explosive gases in the
sample, another property, and combinations thereof.
The detector may include a thermal conductivity sensor, which may
also be referred to herein as a thermal conductivity microhotplate
sensor or a thermal conductivity microcantilever sensor. The
detector may further include a processing subsystem configured to
determine a thermal conductivity of the sample at two or more
temperatures based on data obtained from the thermal conductivity
sensor (e.g., based on a response (e.g., an output) of the thermal
conductivity sensor at each of the two or more temperatures). The
thermal conductivity sensor may be exposed to the sample while the
thermal conductivity sensor is at each of a first temperature and
at least a second temperature. A response (e.g., output) of the
thermal conductivity sensor (e.g., a power to maintain each of the
two or more temperatures) may be measured. A change in thermal
conductivity of the sample relative to a baseline (e.g., a
difference in thermal conductivity of the sample relative to a
reference sample (e.g., a baseline such as air, nitrogen (N.sub.2),
oxygen (O.sub.2), carbon monoxide (CO), methane (CH.sub.4), ethane
(C.sub.2H.sub.6), propane (C.sub.3H.sub.8), natural gas, a
flammable gas, etc.)) at each of the two or more temperatures may
be determined based on a difference in power to maintain the
thermal conductivity sensor at each of the first and at least a
second temperature relative to the power to maintain each of the
first and at least a second temperature when the thermal
conductivity sensor is exposed to the reference sample. The
baseline values may be stored in a memory and may comprise values
obtained in a laboratory. In some embodiments, the baseline values
are obtained using a reference thermal conductivity sensor separate
from the thermal conductivity sensor. In some embodiments, the
baseline values are continuously updated during use and operation
of the detector. The response of the thermal conductivity sensor
may be compensated with the baseline values that are stored in
memory, obtained from the baseline thermal conductivity sensor,
obtained from the thermal conductivity sensor, or combinations
thereof. A baseline value of the thermal conductivity sensor may
also be referred to herein as a "thermal conductivity baseline" or
a "baseline thermal conductivity."
An identity of the sample (e.g., one or more components thereof)
may be determined based, at least in part, on a ratio of the
thermal conductivity of the sample while the thermal conductivity
sensor is at a first temperature to the thermal conductivity of the
sample while the thermal conductivity sensor is at a second
temperature. In some embodiments, the identity of the sample may be
determined based on a ratio of the response of the thermal
conductivity sensor to exposure to the sample while the thermal
conductivity sensor is at the first temperature to the response of
the thermal conductivity sensor to exposure to the sample while the
thermal conductivity sensor is at the second temperature. In some
embodiments, a concentration of different components (e.g., gases)
in the sample may be determined based on at least one of the
thermal conductivity at the first temperature and the thermal
conductivity at the second temperature. As used herein, a thermal
conductivity at a particular temperature (e.g., a first
temperature) means and includes a thermal conductivity or a
response of a thermal conductivity sensor to exposure to a sample
when the thermal conductivity sensor is at the particular
temperature (e.g., a first temperature) and exposed to a
sample.
In some embodiments, the detector may include a catalytic sensor
(e.g., a catalytic microhotplate sensor) configured to determine a
reactivity of the sample (e.g., whether the sample includes a gas
that may undergo an exothermic reaction, a temperature of such an
exothermic reaction, an inert gas, or combinations thereof). The
catalytic sensor may be configured to be exposed to the sample
while the catalytic sensor is at the same first temperature and at
least a second temperature described above with reference to the
thermal conductivity sensor. A response (e.g., an output) of the
catalytic sensor (e.g., a power to maintain the catalytic sensor)
at each of the temperatures may be measured and compared to
baseline catalytic responses for each temperature by the processing
subsystem. The baseline catalytic response may include data stored
in memory, baseline data from the catalytic sensor when exposed to
a baseline sample, or a combination thereof. A difference between
the baseline catalytic response and a measured response of the
catalytic sensor (which difference may be referred to herein as "a
catalytic activity") may be an indication of a reactivity of the
sample (e.g., an exothermic event, also referred to herein as a
"light-off" event or a reaction onset). In some embodiments, the
measured response of the catalytic sensor may be an indication of a
flammability of the sample at the temperature at which there is a
difference. In some embodiments, a temperature at which there is a
difference between the baseline catalytic response and the measured
response of the catalytic sensor may be an indication of a presence
of one or more components in the sample. In some embodiments, a
ratio of the response of the catalytic sensor at the first
temperature to the response of the catalytic sensor at the second
temperature may be used to identify one or more components in the
sample. The magnitude of the response of the catalytic sensor at
the first temperature (e.g., when the catalytic sensor is at the
first temperature), the second temperature (e.g., when the
catalytic sensor is at the second temperature), or both may be an
indication of the concentration of one or more gases or vapors in
the sample. In other embodiments, the identity of the one or more
components may be determined based on a ratio of the catalytic
activity at the first temperature to the catalytic activity at the
at least a second temperature and the concentration of the one or
more components may be determined based on a magnitude of the
catalytic activity at the first temperature, the magnitude of the
thermal conductivity at the at least a second temperature, or
both.
In some embodiments, data from the thermal conductivity sensor may
be combined with the data from the catalytic sensor to determine
the composition of the sample. In some such embodiments, the
composition of the sample may be determined based on one or more of
a ratio of the thermal conductivity of the sample at the first
temperature to the thermal conductivity of the sample at the second
temperature, a ratio of the catalytic sensor response at the first
temperature to the catalytic sensor response at the second
temperature, a ratio of the response of the catalytic sensor at one
or more temperatures to a response of the thermal conductivity
sensor at one or more temperatures, and combinations thereof.
The detector may further include a damping sensor (e.g., an inert
microcantilever) configured to determine one or more of a change in
damping (e.g., viscous damping), a change in resonant frequency, a
change in quality factor, a change in bandwidth, a change in a
parameter determined by using an equivalent circuit model (ECM) to
interpret a response of the damping sensor (including, for example,
a series resistance, a series capacitance, a series inductance, a
parallel capacitance, or combinations thereof), or another property
of the damping sensor dispersed in the sample. The change in the
viscous damping, resonant frequency, quality factor, bandwidth,
series resistance, series capacitance, series inductance, and
parallel capacitance may be with reference to a baseline resonant
property when the damping sensor is exposed to a baseline sample
(e.g., air). The viscous damping, resonant frequency, quality
factor, bandwidth, series resistance, series capacitance, series
inductance, parallel capacitance, and combinations thereof of the
damping sensor when exposed to the baseline sample may be referred
to herein as a baseline resonant parameter. The one or more
properties may be used to determine a composition of the sample. By
way of nonlimiting example, a ratio of a change in the resonant
frequency to a change in the quality factor may be an indication of
the composition of the sample (e.g., a presence of one or more
analytes of interest in the sample). In some embodiments, data
obtained from the damping sensor, the thermal conductivity sensor,
and the catalytic sensor may be combined to determine one or more
of the identity of one or more components of the sample, the
composition of the sample, and the concentration of components in
the sample. In further embodiments, the detector may include one or
more microcantilever sensors comprising a coating formulated to
interact with specific analytes and one or more metal oxide
semiconductor microhotplate sensors configured to interact with one
or more specific analytes and may be used to further distinguish
one or more properties of the sample. Responses from each of the
thermal conductivity sensor, the catalytic sensor, the damping
sensor, the one or more microcantilever sensors (e.g., coated
microcantilever sensors), and the one or more metal oxide
semiconductor microhotplate sensors may be compensated for effects
of one or more of temperature, pressure, relative humidity,
absolute humidity, and flowrate (e.g., of the sample).
In some embodiments, the processing subsystem periodically
interrogates the catalytic sensor to measure a response thereof to
exposure to a sample; if an exothermic light-off event is detected,
indicating the presence of one or more flammable gases, the
light-off temperatures are stored in memory and processing, as
described in subsequent paragraphs. If an exothermic light-off
event is not detected, the MOS and coated microcantilever sensors
may be checked for non-flammable gas responses. The TC and VD may
be checked (with the thermal conductivity sensor and the damping
sensor, respectively) for a change relative to a baseline response,
which may be stored in memory. These preliminary responses parse
the responses into flammable gases with their associated light-off
temperature(s), non-flammable gases, a change in TC and VD relative
to air (i.e., whether the TC and VD of the sample is similar or not
similar to air), MOS and coated microcantilevers with and without
cross sensitivities.
In some embodiments, if no gases are detected, then the processing
subsystem establishes new baselines for the catalytic sensor, the
thermal conductivity sensor, and the damping sensor (e.g., the
resonant frequency thereof) prior to the next interrogation of the
sensors. Note that the sensors are only being utilized to detect
and parse the gases up to this point. In other words, the magnitude
of the responses may not be relied upon for identifying the
components of the sample. Therefore, in some embodiments,
deterioration, as well as drift, of the sensor response magnitudes
may not affect the full analysis. The results of the subsequent
processing can be used to compensate the magnitude responses and
also determine if a sensor response has deteriorated to the point
that a fault is reported.
Responsive to detection of a presence of at least one component
(e.g., gas) in the sample, the processing subsystem may be
triggered to measure a power shift of the thermal conductivity
sensor relative to a stored baseline, which measurement is
proportional to the thermal conductivity (TC) change of the sample.
Note that the magnitude of the TC response typically increases with
increasing temperature, so it is useful to use TC values measured
at a high temperature in some embodiments, thus maximizing the
sensitivity of the TC measurements. In other words, in some
embodiments, the thermal conductivity of the sample may be measured
at a high temperature (e.g., greater than about 50.degree. C., such
as greater than about 400.degree. C.) to increase a sensitivity of
the thermal conductivity sensor. The TC variation with temperature
is unique by gas type and can be further used in subsequent
processing as a gas identifier and quantifier.
For detection and identification of non-flammable gases, the
resonant frequency of the damping sensor (which may be proportional
to VD) and TC can be monitored and compared to baseline data from
previous measurements. When a shift in VD or TC is detected,
further processing can be triggered as described below.
The processing subsystem may compensate the sensors for
temperature, pressure, humidity (relative humidity, absolute
humidity, or both), and flowrate of the sample. Sensor calibration
data may be stored in a non-volatile memory. Data from separate
temperature, pressure, humidity, and flowrate sensors can be
utilized to compensate the individual sensors. Alternately, another
microcantilever can be used to sense temperature, pressure,
humidity, and flowrate. In the case of the catalytic sensor,
subtraction of the thermal conductivity sensor response from the
response of the catalytic sensor compensates the catalytic sensor
for the effects of thermal conductivity, temperature, pressure,
humidity, as well as for the effects of gas flow.
With the data collected and processed as described thus far, the
processing subsystem can determine the magnitude and slope of the
power shift of the thermal conductivity sensor, (which may be
proportional to TC) versus extracted parameters of resonant
frequency shift of the damping sensor (e.g., quality factor (Q),
and R.sub.m (proportional to VD and density)) vector; the vector
magnitude being proportional to gas concentration and the vector
slope being an indicator of the gas identity. In other words, the
ratio of the change in power of the thermal conductivity sensor
(i.e., the change in thermal conductivity of the sample relative to
the baseline) to the change in resonant frequency or viscous
damping of the damping sensor may be used to determine composition
of the sample. Some gases have similar or overlapping TC versus
viscous damping vectors, hence exothermic light-off temperatures
and magnitudes, or lack thereof, together with the MOS and coated
microcantilever responses, or lack thereof, are utilized to further
differentiate gases. For instance, hydrogen and methane have
similar slopes (i.e., the ratio of the change in power of the
thermal conductivity sensor to the change in resonant frequency or
damping (e.g., viscous damping)), but hydrogen has a light-off
temperature typically below 100.degree. C. while methane has a
light-off temperature typically above 400.degree. C., the exact
temperatures being dependent on the catalyst composition used on
the catalytic sensor. Furthermore, in some embodiments, it is
contemplated that multiple light-off events at different
temperatures indicate the presence of multiple flammable gases.
Helium is an example of a non-flammable gas that has a similar TC
vs. VD vector slope to hydrogen and methane, but is parsed by the
fact that no exothermic light-off is detected since it is
non-flammable. The unique TC versus temperature vector can be
utilized to further quantify and identify both flammable and
non-flammable gases.
Once one or more components of the sample are identified, the TC
versus VD magnitude data can be calibrated by the component type to
determine the concentration (e.g., gas concentration) of each
component in the sample. In some embodiments, calibrating the
sensor for each component may be beneficial since the magnitude
response may be dependent on the gas type. In some embodiments, the
memory may include calibration values that may be used for
determining a concentration of one or more components in the sample
based on the particular component identified. The concentration of
the component may be determined based on the calibration value, the
value of the damping (e.g., the viscous damping), and the value of
the thermal conductivity of the sample. With the components of the
sample identified and quantified, the processing subsystem can
cross correlate individual sensor responses to detect faults,
compensate sensors, and update calibration data as required. For
example, the magnitude response of the catalytic sensor can be
compared to the TC versus VD vector magnitude (gas concentration)
to compensate for catalytic response degradation. If the magnitude
response of the catalytic sensor compared to the magnitude of the
TC versus VD vector is below a preset threshold, a fault of the
catalytic sensor can be reported.
As a final analysis, all the sensor responses can be processed
simultaneously in a multi-dimensional analysis and compared to a
stored response database or fingerprint. If a gas separation
device, such as a gas chromatograph (GC), is used ahead of the
detector, the time sequence of the fingerprint response can be used
to further parse the gas identification and quantification.
The processing described above in this embodiment can be repeated
on a periodic basis as required by the application. Between
processing, the system can be powered down or put into a sleep mode
to conserve power. Results of the analysis can be reported and
updated through a communications port or graphical user interface
(GUI).
Accordingly, a multi-dimensional orthogonal data set including, for
example, exothermic light-off temperature(s), exothermic heat, a
ratio of a response of the catalytic sensor at a first temperature
to the response thereof at a second temperature, a catalytic
activity at a first temperature, a catalytic activity at a second
temperature, a ratio of the catalytic activity at the first
temperature to the catalytic activity at the second temperature, TC
(e.g., thermal conductivity at two or more temperatures and a ratio
of the thermal conductivity at a first temperature to the thermal
conductivity at a second temperature), TC versus temperature,
damping (e.g., viscous damping), resonant frequency shift of a
damping sensor, quality factor, equivalent circuit model parameter
shifts, and MOS and coated microcantilever responses is parsed and
analyzed. The system and method described herein overcomes many of
the individual sensor shortcomings. Combining and analyzing the
data enables differentiating gases with similar two-dimensional
characteristics. The resulting detector system is robust,
sensitive, and accurate.
FIG. 1 is an overall block diagram of a detector 100, in accordance
with some embodiments of this disclosure. In one example, sensor
components of the detector 100 may include at least one catalytic
sensor 112 (e.g., a catalytic microhotplate sensor), at least one
thermal conductivity sensor 114, one or more of a metal oxide
semiconductor (MOS) sensor and a coated microcantilever sensor 115,
a damping sensor 116, and one or more environmental sensors 118. In
some embodiments, the thermal conductivity sensor 114 comprises a
reference thermal conductivity sensor configured to measure a
baseline thermal conductivity of a sample and at least another
thermal conductivity sensor separate from the reference thermal
conductivity sensor. In some embodiments, each of the catalytic
sensor 112, the thermal conductivity sensor 114, the one or more of
the metal oxide semiconductor sensor and the coated microcantilever
sensor 115, the damping sensor 116, and the one or more
environmental sensors 118 are disposed on the same substrate (e.g.,
a silicon substrate). A processing subsystem 140 (also referred to
herein as a "subsystem") may be interfaced to analog-to-digital
(A/D) and digital-to-analog (D/A) converters 120 though a data bus
122 to the individual sensors 112, 114, 115, 116, and 118. The
processing subsystem 140 may include a central processing unit
(CPU) 124, a memory 128 (including software, databases, baseline
data, calibration data, etc.), a communications port 130, and
optionally a graphical user interface (GUI) 126. In some
embodiments, flame arrestors, filters, gas-preconcentrators, and/or
separation devices 110 may be used between some or all of the
sensors 112, 114, 115, 116, 118 and the gas sample being analyzed.
The flame arrestor may reduce a likelihood or even prevent a fire
or explosion in flammable environments. The filter may be used to
mitigate or eliminate known sensor contaminants and may be used to
provide enhanced selectivity. The combined filter and flame
arrestor may also be designed to regulate gas flow or diffusion of
the sample to the sensors 112, 114, 115, 116, 118. In some
embodiments, a gas pre-concentrator or a separation device, as
indicated at 110, such as a gas chromatograph, a pump system, or
both may be used ahead of the sensor devices to enhance selectivity
of gases to which the sensors 112, 114, 115, 116, 118 are exposed,
as illustrated at block 110.
As will be described herein, one or more components (e.g., sensors)
of the detector 100 may be used to determine one or more properties
of the sample (e.g., a presence of at least one analyte (e.g., a
gas) of interest, a composition of the sample, a concentration of
one or more analytes in the sample, an average molecular weight of
the sample, etc.).
FIGS. 2A and 2B are a top view and cross-sectional view,
respectively, of a microhotplate sensor 200. FIG. 2B is a
cross-sectional view of the microhotplate sensor 200 taken along
section line B-B in FIG. 2A. The microhotplate sensor 200 may be
used for both the at least one catalytic microhotplate sensor 112
(FIG. 1) and the at least one thermal conductivity sensor 114 (FIG.
1), which may also be referred to herein as a thermal conductivity
microhotplate sensor. In other words, the detector 100 (FIG. 1) may
include at least one microhotplate sensor 200 comprising the
catalytic microhotplate sensor 112 (FIG. 1) and at least another
microhotplate sensor 200 comprising the thermal conductivity sensor
114 (FIG. 1).
The microhotplate sensor 200 may be fabricated on a silicon
substrate 210 using MEMS fabrication techniques. Tethers 224 may
support a suspended microhotplate 226, which may be between 50
.mu.m and about 1,000 .mu.m in diameter. In some embodiments, the
tethers 224 may comprise silicon nitride, silicon dioxide, silicon
carbide, another material, or combinations thereof. A resistive
heater 218 may be suspended over the microhotplate 226 and may be
configured to provide heat to the microhotplate 226 to control a
temperature thereof. A passivation coating 220 may overlie the
resistive heater 218 and a coating material 222 may overlie the
passivation coating 220. The coating material 222 may be isolated
from electrical contact with the resistive heater 218 with a
passivation coating 220. In embodiments where the microhotplate
sensor 200 corresponds to a catalytic sensor 112 (FIG. 1), the
coating material 222 may comprise a catalytic material, such as,
for example, palladium, platinum, ruthenium, silver, iridium,
another catalyst metal, or combinations thereof. The coating
material 222 may further include a support material, such as
aluminum oxide (Al.sub.2O.sub.3), magnesium oxide (MgO), zirconia
(ZrO.sub.2), ceria-stabilized zirconia (CSZ), another support
material, or combinations thereof. In embodiments where the
microhotplate sensor 200 comprises a thermal conductivity sensor
114 (FIG. 1), the coating material 222 may comprise an inert
material. By way of nonlimiting example, the inert coating material
222 may comprise aluminum oxide (Al.sub.2O.sub.3). In other
embodiments of the thermal conductivity sensor 114, the coating
material 222 may not be present. In other embodiments, a membrane
type microhotplate (without tethers; not shown) could be
utilized.
The silicon substrate 210 may include a gap 212 between and under
the silicon tethers 224 and the microhotplate 226. The gap 212 and
the tethers 224 may be configured to minimize or reduce heat loss
from the microhotplate 226 to the substrate. In other words, the
gap 212 and the tethers 224 may provide thermal isolation of the
microhotplate 226 and the resistive heater 218 from the substrate
210 and the tethers 224, which may increase heat transfer to a
sample located proximate the microhotplate 226 and the resistive
heater 218. The resistive heater 218 may be electrically coupled to
bond pads 214 with interconnects 216 that may comprise an
electrically conductive material.
The resistive heater 218 may be powered with a current provided
between the bond pads 214, which may also be referred to as "i+"
and "i-" bond pads 214. Voltage across the resistive heater 218 may
be sensed via bond pads 219, which may also be referred to herein
as "kelvin" bond pads 219, "K+" and "K-." The interconnects 216
associated with the bond pads 219 may be referred to as "kelvin
sense lines." In other embodiments, the voltage across the
resistive heater 218 may be measured elsewhere in the microhotplate
sensor 200 without the kelvin sense lines, but additional
compensation might be necessary to improve measurement
accuracy.
Heater resistance, proportional to temperature, of the
microhotplate 226, and the heater power may be calculated from the
forced current value and measured voltage value. By way of
nonlimiting example, the resistance of the resistive heater 218 may
be determined according to Ohm's law, as shown in Equation (1)
below: R=V/I (1), wherein V is the voltage across the resistive
heater 218 (measured with the bond pads 219) and I is the current
applied to the resistive heater 218 through the bond pads 214. The
power to the resistive heater may be determined according to
Equation (2) below: P=IV (2), wherein P is the power to the
resistive heater 218, and I and V are the same as described
above.
The described microhotplate structure may be optimized to operate
at low power levels (e.g., from about 5 mW to about 50 mW) over a
large temperature range with minimal conductive heat losses,
minimal thermal-mechanical deformations, and good thermal symmetry
and uniformity.
With further reference to FIG. 1, FIG. 2A, and FIG. 2B, the thermal
conductivity sensor 114 (FIG. 1) may be fabricated on the same
silicon wafer as the catalytic sensor 112 (FIG. 1), and may include
identical features as the catalytic sensor 112 except that the
thermal conductivity sensor 114 may not include the coating
material 222 or may include a substantially inert coating material
222. The thermal conductivity sensor 114 may include a
non-catalytic coating (e.g., a substantially inert coating
material) that is used to match the thermal mass, emissivity,
and/or thermal conductivity of the catalytic sensor and/or to
further increase the surface area thereof.
In some embodiments, the resistive heater 218 of each of the
catalytic sensor 112 (FIG. 1) and the thermal conductivity sensor
114 (FIG. 1) may be ramped in predetermined temperature steps by
the processing subsystem 140 (FIG. 1) or a controller and the power
to achieve each temperature step may be monitored by measuring the
voltage and current to the resistive heater 218, as described above
with reference to Equation (2). In some embodiments, the central
processing unit 124 (FIG. 1) comprises a controller configured to
ramp the temperature of the at least one thermal conductivity
sensor 114 (FIG. 1) to a predetermined temperature while the at
least one thermal conductivity sensor is exposed to the sample. The
predetermined temperature may be at least about 400.degree. C., at
least about 600.degree. C., at least about 800.degree. C., at least
about 1,000.degree. C., or at least about 1,200.degree. C.,
although the disclosure is not so limited.
The power at each temperature may be measured and may be correlated
to a thermal conductivity of the sample to which the thermal
conductivity sensor 114 is exposed. Accordingly, the thermal
conductivity sensor 114 may be ramped according to predetermined
temperature steps. In some embodiments, the predetermined
temperature steps may include two or more temperatures. At each
temperature, the voltage across the resistive heater 218 may be
measured (e.g., with the bond pads 219 of the respective
microhotplate sensors 200). From the known current provided to the
microhotplate sensor 200, the resistance and the power of the
microhotplate sensor 200 may be determined for each temperature
(e.g., according to Equation (1) and Equation (2), respectively,
above).
A thermal conductivity or a change in thermal conductivity relative
to a reference gas (e.g., air) may be determined with the thermal
conductivity sensor 114 (FIG. 1). A difference in the thermal
conductivity between a sample (e.g., a sampled gas) and a reference
(e.g., a baseline) gas may be determined according to Equation (3)
below: .DELTA.TC=TC(n)TC(baseline) (3), wherein TC(n) is the
response of the thermal conductivity sensor 114 (e.g., a power to
the thermal conductivity sensor 114 to maintain a particular
temperature) to exposure to a sample while the thermal conductivity
sensor is at the particular temperature, TC(baseline) is one or
more of the thermal responses of the thermal conductivity sensor
114 data from previous temperature ramps (e.g., the baseline data,
such as an average of TC(n) at the particular temperature such as
when the thermal conductivity sensor 114 is exposed to a baseline
or a reference sample (e.g., air)), a response of a reference
thermal conductivity sensor to exposure to a reference sample, and
baseline data stored in memory, and .DELTA.TC is the relative
change in the response of the thermal conductivity sensor 114 at
the particular temperature relative to the baseline value
(TC(baseline)) at the particular temperature and may be referred to
herein as a change in thermal conductivity at a particular
temperature. The baseline data (TC(baseline)), typically stored in
memory, may be determined in a laboratory or may comprise an
average value of the response of the thermal conductivity sensor or
a reference thermal conductivity sensor from previous measurements
for each temperature of interest. The baseline or reference sample
may include air, oxygen, nitrogen, carbon monoxide, methane,
natural gas, ethane, propane, another gas, or combinations thereof.
A change in the power to maintain each temperature relative to the
baseline (e.g., the value of .DELTA.TC) may be an indication of a
change in the thermal conductivity of the sample relative to a
baseline (e.g., air). In some embodiments, .DELTA.TC may be
determined at two or more temperatures. In some embodiments,
.DELTA.TC may be determined during the temperature ramp and at
temperature intervals (e.g., about every 100.degree. C., about
every 50.degree. C., about every 25.degree. C., about every
10.degree. C., about every 5.degree. C., or even every about
1.degree. C.). In some embodiments, the baseline or reference
sample may be selected based on a desired use of the detector. By
way of nonlimiting example, a detector may be used to determine a
content of natural gas and the baseline of such sensor may comprise
methane or natural gas. Changes in the thermal conductivity
relative to the baseline may correspond to changes in a composition
of natural gas. Accordingly, the baseline may be selected based on
a desired use of the detector.
In some embodiments, baseline historical data from the thermal
conductivity sensor 114, stored in memory 128, from previous
reference ramps may be subtracted from the current reference ramp
to produce a signal representative of the thermal response
(.DELTA.TC). The .DELTA.TC power measurements from the thermal
conductivity sensor 114 may be directly proportional to the TC of
the gas and may be measured at two or more temperatures. It can be
advantageous to measure TC at relatively low temperatures (e.g.,
from about 50.degree. C. to about 250.degree. C.) and also at
relatively high temperatures (e.g., from about 400.degree. C. to
about 800.degree. C.).
FIG. 3A is a graph illustrating a change in thermal conductivity of
several gases at a first temperature and the change in thermal
conductivity of the gases as a second temperature relative to a
baseline (e.g., air). A thermal conductivity of 0 corresponds to
the thermal conductivity of air at the plotted temperature. A
negative thermal conductivity indicates a negative shift (i.e., a
decrease) in thermal conductivity relative to air and a positive
thermal conductivity indicates a positive shift (i.e., an increase)
in thermal conductivity relative to air. A thermal conductivity
sensor 114 (FIG. 1) was exposed to the gases and the thermal
conductivity change relative to air of each gas was determined
according to Equation (3) above. FIG. 3A shows the thermal
conductivity sensor 114 responses to various gases at a first
temperature (200.degree. C.) and a second temperature (710.degree.
C.). As indicated in FIG. 3A, the thermal conductivity change
relative to air for the gases illustrated increases with increasing
temperature.
FIG. 3B is a plot illustrating a change in a thermal conductivity
at a first temperature (at 200.degree. C.) versus a change in a
thermal conductivity at a second temperature (at 700.degree. C.) of
the same gases of FIG. 3A. The data illustrated in FIG. 3B is
normalized to methane at a concentration of 50% lower explosive
limit (LEL). The point (0,0) corresponds to the TC of air without
any analytes. Each gas plotted is for a relative density exposure
of 50% LEL. Since the measurements are normalized to 50% LEL for
methane, the methane endpoint appears at the coordinates of (50,
50). Intermediate points between the origin and the endpoints for
each gas are representative of the sensor's response (e.g., the
power to maintain each of the two temperatures) over time when it
is exposed to the gas being measured. Each gas exhibits a unique
slope of change in thermal conductivity relative to the baseline
(air) at the first temperature to the change in thermal
conductivity relative to the baseline at the second temperature. As
used herein, the terms "change in thermal conductivity relative to
the baseline" and "change in thermal conductivity" are used
interchangeably. As used herein, reference to a thermal
conductivity at a particular temperature includes the change in
thermal conductivity relative to the baseline at the particular
temperature.
Accordingly, the ratio of the change in thermal conductivity at the
first temperature (i.e., the response of the thermal conductivity
sensor to exposure to the sample when the thermal conductivity
sensor is at the first temperature relative to the thermal
conductivity baseline at the first temperature (e.g., .DELTA.TC at
the first temperature)) to the change in thermal conductivity at
the second temperature (i.e., the response of the thermal
conductivity sensor to exposure to the sample when the thermal
conductivity sensor is at the second temperature relative to the
thermal conductivity baseline at the second temperature (e.g.,
.DELTA.TC at the second temperature)) may be unique by gas type.
Accordingly, in some embodiments, a composition of a sample may be
determined based, at least in part, on the ratio of the change in
thermal conductivity at the first temperature to the change in
thermal conductivity at the second temperature. In some
embodiments, the thermal conductivity sensor 114 may be exposed to
a first, relatively lower temperature and a second, relatively
higher temperature and a thermal conductivity (or a change in
thermal conductivity relative to the reference) of the sample may
be determined at each temperature.
FIG. 3C is a graph showing a relationship between a so-called
"k-factor" and the ratio of the change in thermal conductivity at
the first temperature (when the thermal conductivity sensor 114 is
at the first temperature and exposed to a sample) to the change in
thermal conductivity at the second temperature (when the thermal
conductivity sensor 114 is at the second temperature and exposed to
the sample) for a plurality of gases. For each gas, the k-factor
may be equal to a concentration of a gas (for example, in percent
of lower explosive limit (LEL), in parts per million (ppm), etc.)
to which the thermal conductivity sensor is exposed divided by the
magnitude of the response of the thermal conductivity sensor (e.g.,
at the second temperature, such as 700.degree. C.). The k-factor
may be determined in a laboratory and the k-factor for each of a
plurality of gases may be stored in the memory 128 (FIG. 1). In
some embodiments, a composition of the sample may be determined
based on the ratio of the change in the thermal conductivity of the
sample at the first temperature to the change in the thermal
conductivity at the second temperature and the k-factor, which may
be stored in the memory 128 (FIG. 1). In some embodiments, after an
identity of a gas is identified, a concentration thereof may be
determined by multiplying its respective k-value by the thermal
conductivity at a particular temperature (e.g., the response of the
thermal conductivity sensor to exposure to the sample while the
thermal conductivity sensor is at the particular temperature).
After identification of the gas in the sample, in some embodiments,
a concentration of the gas in the sample may be estimated based on
a magnitude of the change in the thermal conductivity relative to
the baseline at the first temperature, the magnitude of the change
in the thermal conductivity relative to the baseline at the second
temperature, or both. In some embodiments, the concentration of the
gas may be determined based on the magnitude of the change of the
thermal conductivity at the first temperature and the magnitude of
the change in thermal conductivity at the second temperature. With
reference to FIG. 3B, each gas may exhibit a specific magnitude for
a given concentration. Accordingly, the length of the vector in
FIG. 3B may be multiplied by the calibration data (i.e., the
k-factor) stored in memory 128 (FIG. 1) to determine the
concentration of the sample.
FIG. 3D is a graph illustrating a relationship between a ratio of
the change in thermal conductivity of the sample at a first
temperature (e.g., a difference in a response of the thermal
conductivity sensor to exposure to the sample when the thermal
conductivity sensor is at the first temperature and a baseline
response of the thermal conductivity sensor to exposure to a
reference when the thermal conductivity sensor is at the first
temperature) to the change in the thermal conductivity of the
sample at the second temperature (e.g., a difference in a response
of the thermal conductivity sensor to exposure to the sample when
the thermal conductivity sensor is at the second temperature and a
baseline response of the thermal conductivity sensor to exposure to
a reference when the thermal conductivity sensor is at the second
temperature) and an average molecular weight of the sample.
Accordingly, in some embodiments, an average molecular weight of
the sample may be determined based on the ratio. In some
embodiments, one or both of a presence of one or more gases and a
concentration of one or more gases in the sample may be determined
based, at least in part, on the average molecular weight. In FIG.
3D, the first temperature is 200.degree. C. and the second
temperature is 700.degree. C.
FIG. 4 is a simplified flow diagram illustrating a method 400 of
using the thermal conductivity sensor 114 (FIG. 1) to determine one
or more properties of a sample (e.g., a composition of the sample).
The method 400 includes act 402 including exposing a thermal
conductivity sensor to a sample while the thermal conductivity
sensor is at a first temperature; act 404 including determining a
thermal conductivity of the sample while the thermal conductivity
sensor is at the second temperature; act 406 including exposing the
thermal conductivity sensor to the sample while the thermal
conductivity sensor is at a second temperature higher than the
first temperature; act 408 including determining a thermal
conductivity of the sample while the thermal conductivity sensor is
at the second temperature; act 410 including determining a ratio of
the thermal conductivity of the sample when the thermal
conductivity sensor is at the first temperature to the thermal
conductivity of the sample when the thermal conductivity sensor is
at the second temperature; and act 412 including identifying a
presence of one or more gases in the sample based, at least in
part, on the value of the ratio.
Act 402 may include exposing a thermal conductivity sensor to a
sample while the thermal conductivity sensor is at a first
temperature. In some embodiments, the thermal conductivity sensor
may be substantially the same as the microhotplate sensor 200
described above with reference to FIG. 2A and FIG. 2B. The thermal
conductivity sensor at the first temperature may be exposed to a
sample including an analyte of interest. At a temperature between
about 150.degree. C. and about 250.degree. C. a first desorbing of
the physisorbed species, especially H.sub.2O, is affected before
ramping to higher temperatures where poisoning chemical reactions
can take place, thus preserving the catalytic coating. In some
embodiments, it can be advantageous to measure TC while the thermal
conductivity sensor 114 is at relatively low temperatures (about
50.degree. C. to about 250.degree. C.) and also at relatively high
temperatures (about 300.degree. C. to about 800.degree. C., such as
between about 400.degree. C. and about 800.degree. C.). The first
temperature may be selected to be above a temperature at which
water may physisorb on the thermal conductivity sensor 114. In some
embodiments, the first temperature may be selected to be between
about 200.degree. C. and about 250.degree. C., such as about
200.degree. C. In some such embodiments, the first temperature is
selected to be above the boiling point of water.
Act 404 may include determining a thermal conductivity of the
sample while the thermal conductivity sensor is at the first
temperature. The thermal conductivity (e.g., the change in thermal
conductivity relative to a baseline) may be determined based on
Equation (3) above. By way of nonlimiting example, the power of the
thermal conductivity sensor to maintain the first temperature may
be measured. The power to maintain the first temperature when the
thermal conductivity sensor is exposed to a reference sample (e.g.,
the baseline value) may be subtracted from the power to maintain
the first temperature when the thermal conductivity sensor is
exposed to the sample. The difference may be proportional to the
change in thermal conductivity of the sample relative to the
baseline (e.g., air). In other words, the difference may correspond
to the difference in thermal conductivity of the sample relative to
the thermal conductivity of the reference.
Act 406 may include exposing the thermal conductivity sensor to the
sample while the thermal conductivity sensor is at a second
temperature higher than the first temperature. TC generally
increases with increasing temperatures; therefore measurements made
at high temperatures will give larger responses, thus increasing
the system sensitivity. Accordingly, in some embodiments, the
second temperature may be selected to be greater than about
400.degree. C. The second temperature may be selected to be between
about 300.degree. C. and about 800.degree. C., such as between
about 300.degree. C. and about 400.degree. C., between about
400.degree. C. and about 600.degree. C., between about 600.degree.
C. and about 700.degree. C., or between about 700.degree. C. and
about 800.degree. C.
Act 408 may include determining a thermal conductivity of the
sample while the thermal conductivity sensor is at the second
temperature. Determining the thermal conductivity of the sample
while the thermal conductivity sensor is at the second temperature
may be performed in substantially the same manner as determining
the thermal conductivity of the sample while the thermal
conductivity sensor is at the first temperature described above
with reference to act 404. For example, the power of the thermal
conductivity sensor to maintain the second temperature may be
measured and compared to the power to maintain the second
temperature when the thermal conductivity sensor is exposed to a
reference sample (e.g., the baseline value). The difference may be
proportional to the change in thermal conductivity of the sample
relative to the baseline (e.g., air).
Act 410 may include determining a ratio of the change in the
thermal conductivity of the sample relative to the baseline when
the thermal conductivity sensor is at the first temperature to the
change in the thermal conductivity of the sample relative to the
baseline when the thermal conductivity sensor is at the second
temperature. The ratio may be determined according to Equation (4)
below: R.sub.TC=TC.sub.T1/TC.sub.T2 (4), wherein R.sub.TC is the
ratio, TC.sub.T1 is the change in the thermal conductivity at the
first temperature, and TC.sub.T2 is the change in the thermal
conductivity at the second temperature. In some embodiments,
TC.sub.1 is equal to .DELTA.TC at the first temperature and
TC.sub.2 is equal to .DELTA.TC at the second temperature according
to Equation (3) above.
Act 412 includes identifying an identity of one or more analytes in
the sample based, at least in part, on the value of the ratio. In
some embodiments, and with reference to FIG. 3B, the value of the
ratio may be indicative of a presence of one or more components
(e.g., gases) in the sample. In some embodiments, the method 400
further includes determining a concentration of one or more gases
in the sample. The concentration of the one or more gases may be
determined based on one or more of the change in the thermal
conductivity at the first temperature, the change in the thermal
conductivity at the second temperature, or both. In some
embodiments, the concentration of the gas may be determined based
on Equation (5) below:
C=k((TC.sub.T1).sup.2+(TC.sub.T2).sup.2).sup.1/2 (5), wherein k is
an empirically determined k-factor as described above, C is the
concentration of the gas, TC.sub.T1 is the change in the thermal
conductivity of the sample at the first temperature, and TC.sub.T2
is the change in the thermal conductivity of the sample at the
second temperature. More generally, when using magnitudes of n
parameters, P, the concentration can be determined according to
Equation (6) below: C=k((P.sub.1).sup.2+(P.sub.2).sup.2+ . . .
(P.sub.n).sup.2).sup.1/2 (6), Therefore, if using only the single
parameter, TC.sub.T1, the concentration may be determined by
C=k((TC.sub.T1).sup.2).sup.1/2=kTC.sub.T1. In some embodiments,
parameters that may be used to determine a concentration of one or
more gases in the sample include a change in resonant frequency of
a damping sensor, a change in quality factor of a damping sensor, a
change in series resistance (.DELTA.R.sub.m) of a damping sensor, a
change in thermal conductivity at a first temperature, a change in
thermal conductivity at a second temperature, a catalytic activity
at the first temperature, a catalytic activity at the second
temperature, a reactivity at a first temperature, a reactivity at a
second temperature, another parameter, or combinations thereof.
In some embodiments, a presence of one or more gases in a sample
may be determined by a change of the thermal conductivity of the
sample as a function of temperature. For example, referring to FIG.
5A, a graph of TC versus temperature is illustrated showing TC
versus temperature vectors for several gases, which is unique by
gas type. In some embodiments, some gases may be differentiated
based on a ratio of their thermal conductivity to temperature, the
thermal conductivity at one or more temperatures, or both. The data
for TC versus temperature may be collected from the thermal
conductivity sensor 114 (FIG. 1) during the temperature ramp,
previously discussed with reference to Equation (3) above. The
slope and magnitude of the TC versus temperature vector, unique by
gas, can be used as an additional analysis dimension for
identifying and quantifying the sampled gas. FIG. 5B is another
graph illustrating a relationship between thermal conductivity of
some gases and temperature. In FIG. 5B, it can be seen that the
methane trace remains above that of air at all temperatures tested,
whereas the propane trace starts below air at lower temperatures
but crosses over air midway up the ramp. The temperature associated
with this crossover feature and other such features can be used to
identify gases, while the magnitude of the TC measurement (usually
relative to a change from a baseline TC value of pure air) can be
used to quantify the concentration of gases present in the air.
There are multiple ways to measure the TC of a sample. One method
is to hold the sensor (e.g., the thermal conductivity sensor 114
(FIG. 1)) at a target temperature (e.g., 700.degree. C.) and
measure the power required to maintain this temperature--where
higher power correlates to higher thermal conductivity due to the
higher energy lost due to conduction from the sensor to the gas,
and vice versa. Another method entails ramping the sensor
temperature while measuring TC. As shown in FIG. 5A and FIG. 5B,
the TC variation with temperature is unique by gas type. As such,
measuring the TC at multiple temperatures can yield gas-specific
sensor outputs like those shown in FIG. 3A, FIG. 3B, FIG. 5A, and
FIG. 5B.
The temperature at which a thermal conductivity of a gas crosses
the TC of air can be leveraged in additional ways. For instance,
the TC of water vapor crosses the TC of air at about 290.degree. C.
(563K in FIG. 5A). Making TC measurements at 290.degree. C. may
reduce or even substantially eliminate the effect of humidity in
the TC measurements. Alternatively, a separate humidity measurement
can be used to compensate measurements made at other temperatures,
and thus the air to air-gas mixture TC crossing temperature can be
used as a gas identifier.
It is contemplated that, in some embodiments, some gases may
exhibit similar ratios of a change in thermal conductivity at a
first temperature to a change in thermal conductivity at a second
temperature, magnitudes of change in thermal conductivity at the
first temperature and/or second temperature, k-factors, or
relationship between temperature and thermal conductivity. In some
such embodiments, at least one property of the sample may be
determined based on one or more responses received from the
catalytic sensor 112 (FIG. 1). In some embodiments, the catalytic
sensor 112 (FIG. 1) may be exposed to a temperature ramp including
the same temperatures to which the thermal conductivity sensor 114
(FIG. 1) is exposed, as described above with reference to FIG. 4.
Baseline data from the catalytic sensor 112 may be subtracted from
each new measurement to produce a signal representing changes in
the response of the catalytic sensor (e.g., change in a catalytic
thermal response (Delta Cat)) relative to a baseline response of
the catalytic sensor 112 for each temperature of a plurality of
temperatures, according to Equation (7) below: Delta
Cat=Cat(n)-Cat(baseline) (7), wherein Delta Cat is the relative
change in response of the catalytic sensor 112 (e.g., a change in
the power to the catalytic sensor 112 relative to the baseline),
Cat(n) is the response of the catalytic sensor 112 to exposure to
the sample (e.g., the power to maintain a predetermined temperature
while the catalytic sensor 112 is exposed to the sample), and
Cat(baseline) is one or more of the response of the catalytic
sensor 112 to exposure to a baseline or a reference gas (e.g., air)
and data stored in memory (e.g., calibration data). Delta Cat may
be referred to herein as a "catalytic activity" of the catalytic
sensor 112 at a particular temperature responsive to exposure to
the sample. Cat(n) may be referred to herein as the "catalytic
response" of the catalytic sensor 112 or a response of the
catalytic sensor 112 to exposure to the sample at a particular
temperature. Baseline data from the catalytic sensor 112 may be
referred to herein as a "catalytic baseline" or a "baseline
catalytic response." The Cat (baseline) may comprise a historic
average value of the power to maintain a temperature the resistive
heater 218 (FIG. 2A, FIG. 2B) of the catalytic sensor 112 at the
temperature of interest when the catalytic sensor 112 is exposed to
the reference sample and may be continuously updated during each
temperature ramp. The Delta Cat, Cat(n), and Cat(baseline) values
may be determined for each temperature of a plurality of
temperatures. The baseline data may include values of power to
maintain each temperature of the temperature ramp, for each of the
thermal conductivity sensor 114 and the catalytic sensor 112.
Accordingly, the baseline data may be stored in memory 128 (FIG. 1)
and may consist of historical power versus temperature data from
previous temperature ramps of the catalytic sensor 112.
The Delta Cat (the catalytic activity of the catalytic sensor 112)
value may be determined at each temperature during the temperature
ramp. Accordingly, Delta Cat may correspond to a difference in
power to maintain a given temperature of the catalytic sensor 112
while the catalytic sensor 112 is exposed to the sample relative to
the catalytic baseline or the power to maintain the given
temperature when the catalytic sensor 112 is exposed to the
reference gas. In some embodiments, a Delta Cat value that deviates
from zero or has a magnitude greater than a predetermined threshold
may be an indication of a reactivity of the sample and may
correspond to, for example, a reaction on the catalytic sensor 112
(i.e., an exothermic reaction), a reaction onset (e.g., an
ignition) temperature of an analyte in contact with the catalytic
sensor 112, or both. Multiple catalytic sensors, some having
different catalyst formulations with differing sensitivities, can
also be utilized.
The catalytic sensor 112 and thermal conductivity sensor 114 (FIG.
1) may be ramped simultaneously to obtain measurements that are
correlated in time for improved sensor measurement accuracy.
The .DELTA.TC measurement (Equation (3)) may be subtracted from the
Delta Cat measurement (Equation (7)), the resultant difference
producing a signal response proportional to the reactivity of the
sample (e.g., the exothermic heat generated on the catalytic
sensor), as shown in Equation (8) below: Exo(new)=Delta
Cat-.DELTA.TC (8), wherein Exo(new) is the signal response that is
proportional to the heat generated on or removed from the catalytic
sensor and Delta Cat and .DELTA.TC are as previously described.
Exo(new) may be referred to herein as a reactivity of the sample or
an exothermic response of the catalytic sensor 112. As used herein,
the term "exothermic response" means and includes a difference
between a catalytic activity of a catalytic sensor and a change in
a response of a thermal conductivity sensor to exposure to a sample
when the thermal conductivity sensor is at a first temperature
compared to a baseline response of the thermal conductivity sensor
when the thermal conductivity sensor is at the first
temperature.
Subtracting the .DELTA.TC signal from the Delta Cat signal may
compensate the Delta Cat signal for the effects of temperature,
pressure, humidity (absolute humidity and relative humidity), and
flow variations of the gas under test. Exo(new) may correspond to a
difference in response (e.g., signal) between the thermal
conductivity sensor 114 and the catalytic sensor 112 at each
temperature for which it is determined. Accordingly, a deviation in
the value of Exo(new) from its nominal value (e.g., an Exo(new)
value different than 0 or greater than a predetermined threshold)
may correspond to an exothermic reaction, a reaction onset, or
both. In some embodiments, the temperature of the light-off is
another identifier of the gas type detected. Multiple light-offs at
differing temperatures is an indication of multiple flammable gases
present in the sample.
The detection of an exothermic reaction (e.g., an exothermic event)
or reaction onset may be used as a flammable gas trigger,
establishing a time zero (T.sub.0), for the subsequent processing
and analysis. As previously noted, in a conventional sensor, the
magnitude of response of the catalytic sensor 112 (FIG. 1) may
deteriorate with time and poisoning. In some embodiments,
determining a presence of a flammable gas according to the methods
described above may be independent of catalyst poisoning. In other
words, the trigger from the catalytic sensor may be independent of
a response magnitude therefrom and may correspond to a binary
yes/no trigger from light-off, along with the light-off temperature
data, that is used in the subsequent processing. Stated another
way, responsive to determining a presence of a flammable gas, such
as by determining an Exo(new) (Equation (8)) value greater than a
predetermined threshold (e.g., a non-zero value) or a difference
between a response of the catalytic sensor 112 and a response of
the thermal conductivity sensor 114, the processing subsystem 140
(FIG. 1) may be triggered to perform analysis of the sample. In
some such embodiments, the processing subsystem 140 may determine
that the baseline thermal conductivity and the baseline catalytic
response (e.g., Cat(baseline)) are the most recent measurements
(outputs) from the respective thermal conductivity sensor 114 and
catalytic sensor 112 measured immediately prior to detection of the
difference in the response of the catalytic sensor 112 and the
thermal conductivity sensor 114. In some such embodiments, analysis
by the processing subsystem 140 may be substantially unaffected by
catalyst poisoning, since the baseline data is continuously
updated. It will be shown later how the magnitude of the catalytic
response can be compensated and calibrated with data from the
subsequent processing.
FIG. 6 is a simplified flow diagram illustrating a method 600 of
determining a composition of a sample, according to some
embodiments of the disclosure. In some embodiments, the method 600
may be performed simultaneously with the method 400 described above
with reference to FIG. 4. The method 600 includes determining a
response of the catalytic sensor 112 (FIG. 1) at two or more
temperatures, which may be the same two or more temperatures used
to determine the response of the thermal conductivity sensor 114
(FIG. 1) described above with reference to FIG. 4. The method 600
may include act 602 including exposing a catalytic sensor to a gas
while the catalytic sensor is at a first temperature; act 604
including determining a response of the catalytic sensor to
exposure to the sample while the catalytic sensor is at the first
temperature; act 606 including exposing the catalytic sensor to the
sample while the catalytic sensor is at a second temperature; act
608 including determining a response of the catalytic sensor to
exposure to the sample while the catalytic sensor is at the second
temperature; and act 610 including determining at least one
property of the sample based, at least in part, on the response of
the catalytic sensor at one or both of the first temperature and
the second temperature.
Act 602 may include exposing a catalytic sensor to a sample while
the catalytic sensor is at a first temperature. In some
embodiments, act 602 includes exposing the catalytic sensor to the
sample while the catalytic sensor is at the first temperature,
which may correspond to the same first temperature to which the
thermal conductivity sensor 114 (FIG. 1) is exposed. In some
embodiments, the catalytic sensor may be exposed to the sample
while the catalytic sensor is at a temperature between about
200.degree. C. and about 250.degree. C.
Act 604 may include determining a response of the catalytic sensor
to exposure to the sample while the catalytic sensor is at the
first temperature. In some embodiments, act 604 includes
determining the catalytic activity of the catalytic sensor and the
exothermic response of the catalytic sensor, which may be
determined according to, for example, Equation (7) and Equation
(8), respectively, above. Act 606 may include exposing the
catalytic sensor to the sample while the catalytic sensor is at a
second temperature (e.g., about 700.degree. C.) and act 608 may
include determining a response of the catalytic sensor responsive
to exposure to the sample while the catalytic sensor is at the
second temperature. In some embodiments, act 608 may include
determining the catalytic activity of the catalytic sensor and the
exothermic response of the catalytic sensor to exposure to the
sample at the second temperature. In some embodiments, the second
temperature may be selected to be the same second temperature to
which the thermal conductivity sensor 114 (FIG. 1) is exposed in
act 406 described above with reference to FIG. 4.
In some embodiments, act 602 through act 608 may be performed
simultaneously with act 402 through act 406 described above with
reference to FIG. 4.
Act 610 may include determining at least one property of the sample
based, at least in part, on the response of the catalytic sensor at
one or both of the first temperature and the second temperature. In
some embodiments, determining the at least one property may further
include determining the at least one property based on the
catalytic activity of the catalytic sensor at the first
temperature, the catalytic activity of the catalytic sensor at the
second temperature, the exothermic response at the first
temperature (the reactivity of the sample at the first
temperature), the exothermic response at the second temperature
(the reactivity of the sample at the second temperature), a ratio
of the catalytic activity at the first temperature to the catalytic
activity at the second temperature, and a ratio of the exothermic
response at the first temperature to the exothermic response at the
second temperature. In some embodiments, the gas identity (e.g., a
presence of at least one component in the sample) may be determined
based, at least in part, on a ratio of the response of the
catalytic sensor at the first temperature to the response at the
second temperature. By way of nonlimiting example, the gas may be
identified based, at least in part on the value of the Exo(new) at
the first temperature to the value of Exo(new) at the second
temperature.
With reference now to FIG. 1, FIG. 7A, and FIG. 7B, the detector
100 may further include the damping sensor (e.g., an inert
microcantilever) 116 and a coated microcantilever sensor 115. As
used herein, an "inert microcantilever" means and includes a
microcantilever including either a substantially inert coating
material (i.e., a coating material that does not substantially
interact (e.g., react) with the sample) or a microcantilever
without a coating material. Depending on the fabrication process,
the damping sensor 116 and the coated microcantilever sensor 115
may be fabricated on the same silicon wafer as the thermal
conductivity sensor 114 and the catalytic sensor 112, or on a
separate substrate. Multiple microcantilevers of various sizes,
shapes, and materials can be utilized for redundancy and response
optimization for the environment in which they are designed to
operate. To improve sensitivity to specific analytes, a coating
material 764 may be applied to a free end 730 of the
microcantilever.
FIG. 7A and FIG. 7B are a respective top down view and
cross-sectional view of a microcantilever sensor 700. The
microcantilever sensor 700 may correspond to the damping sensor 116
and the coated microcantilever sensor 115 described above with
reference to FIG. 1. The microcantilever sensor 700 may be
fabricated on a silicon substrate 760 (which may be the same as the
silicon substrate 210 (FIG. 2A, FIG. 2B) on which the thermal
conductivity sensor 114 and the catalytic sensor are formed)
utilizing MEMS fabrication techniques. The microcantilever sensor
700 shown in FIG. 7A is a dual beam cantilever with a gap 710 in
the substrate 760 near the base end to form the two beams that are
connected at the free end 730. A base silicon material 762 (e.g.,
substrate) is also etched around and under the cantilever to
suspend the free end 730 of the cantilever, allowing the free end
730 of the microcantilever 700 to move and vibrate responsive to
interaction with a sample. Although FIG. 7A illustrates that the
microcantilever 700 includes a gap 710, the disclosure is not so
limited and in some embodiments, the microcantilever may not
include a gap. Although FIG. 7A and FIG. 7B illustrate that the
microcantilever 700 is a dual beam microcantilever, a single beam
microcantilever or a different shaped microcantilever (not shown)
can also be utilized. The microcantilever sensor 700 may be driven
(e.g., vibrated) by applying a voltage through bond pads 724
connected to a piezoelectric element 740. The vibration or flexure
may be sensed with the same piezoelectric element, or may be sensed
with a piezoresistive element 756, which may be electrically
coupled to another pair of bond pads 724. The piezoelectric element
740 may comprise a layer of silicon with a thin layer of aluminum
nitride, zinc oxide or PZT disposed on one side of the silicon
layer. Zinc oxide may be deposited on microcantilever sensor 700
using, for example, a sputtering process. PZT may be deposited on
microcantilever sensor 700 using, for example, a sol-gel process.
In another example, the piezoelectric element 740 comprises a layer
of silicon nitride with a patterned piezoelectric film on one side
of the silicon nitride layer. Two thin layers of a metal such as
gold or platinum may be positioned on each side of the patterned
piezoelectric element 740, providing electrical contact to the
piezoelectric element 740.
In another example, the microcantilever sensor 700 includes the
piezoresistive element 756 near the fixed end there thereof. The
piezoresistive element 756 may be used to detect vibration in the
microcantilever sensor 700 and can also be used to thermally excite
vibration in the microcantilever sensor 700 instead of using a
piezoelectric sense and drive (i.e., rather than using the
piezoelectric element 740 as both a drive element and a sensing
element). The piezoresistive element 756 may be formed on a layer
of single-crystal silicon by depositing a polycrystalline silicon
with a dielectric layer such as silicon dioxide positioned between
the single-crystal silicon layer and the piezoresistive layer. In
another example, a piezoresistor is formed in or near a surface of
a single-crystal silicon cantilever. In another example, the
piezoresistive element 756 comprises a thin film metal.
In some embodiments, the microcantilever sensor 700 includes a
resistive heater 758 on or near the surface of the free end 730 of
the microcantilever sensor 700. The resistive heater 758 may be
formed using similar processes as described for the piezoresistive
element 756. The resistive heater 758 may be used to heat the
microcantilever sensor 700 for making measurements at an elevated
temperature, to heat the microcantilever sensor 700 for cleaning,
to sense the temperature of the microcantilever 700, and also be
used to heat a coating material 764 to initiate an analyte reaction
with between the coating material 764 and at least one analyte of
interest in the sample. In some embodiments, the resistive heater
758 may be configured to clean the microcantilever sensor 700 and
desorb analytes from the coating material 764. The resistive heater
758 can also be a piezoresistive element formed with doped silicon
near the surface of the microcantilever 700 or a thin metal film
deposited on the surface of the microcantilever 700. The resistive
heater 758 can also be used to sense the temperature of the
microcantilever 700.
Passivation layer 746 may be disposed over the resistive heater
758, the piezoresistive element 756, the piezoelectric element 740,
and the interconnecting wiring to electrically isolate those
elements from samples exposed to the microcantilever sensor 700.
Voids in a passivation layer 726 over the bond pads 724 allow wire
bonding to the bond pads 724. It is preferred that the surface of
the microcantilever sensor 700 be chemically non-reactive with the
gases under test when using the microcantilever to sense viscous
damping.
In embodiments where the microcantilever sensor 700 comprises a
coated microcantilever sensor 115 (FIG. 1), the coating material
764 may include a catalytic coating material formulated to interact
with one or more analytes. In embodiments where the microcantilever
sensor 700 comprises a damping sensor 116 (FIG. 1), the
microcantilever sensor 700 may not include a coating material or
may include a substantially inert coating material 764. In some
such embodiments, the primary function of damping sensor 116 is to
measure the damping (e.g., viscous damping) of the microcantilever
sensor 700 in the sampled gas, which may be proportional to a
density of the sampled gas, by detecting changes in the resonant
characteristics of the damping sensor 116. In some embodiments, a
size of the microcantilever sensor 700 may be minimized to reduce
an amount of adsorption of the sample thereon.
A cantilever oscillating in a fluid such as air may be subject to
dissipative forces that retard its motion and rob it of energy.
These forces are known as damping, and affect the cantilever's
resonant frequency, quality factor, series resistance, inductance,
and other characteristic parameters of its resonance response (its
oscillatory amplitude as a function of forcing frequency). For a
cantilever resonating in air at standard conditions, the dominant
damping mechanism is viscous damping (VD). The amount of damping
(e.g., VD) varies to equal degrees with the density and the dynamic
viscosity of the fluid through which the cantilever (e.g., beam)
moves. As such, measuring the resonance response of a cantilever is
a means of measuring the damping (e.g., VD) characteristic of a
given sample, or of monitoring the presence of other gases and
vapors in the sample, observed as changes in damping (e.g., viscous
damping) compared to air alone. Moreover, the measurement and
analysis of multiple resonance parameters can enable deconvolution
of the two primary physical properties of the fluid that govern
viscous damping (density and viscosity). In some embodiments, the
damping sensor 116 may be configured to operate in a plurality of
resonant modes, such as high frequency resonance modes beyond the
fundamental mode. Higher-order flexural modes may have different
sensitivities to damping effects, and may be useful in compensating
for environmental effects (e.g., effects of one or more of
temperature, pressure, relative humidity, and absolute humidity).
Higher modes may also exhibit higher quality factors, for improved
resolution of Q and resonant frequency.
Referring to FIG. 7C, at least some of the resonant characteristics
(resonant parameters) of the damping sensor 116 (FIG. 1) may be
extracted from an equivalent circuit model (ECM) of the electrical
response thereof. The equivalent circuit model may include a
resonant frequency (F.sub.r, also referred to as .omega..sub.r), a
series resistance (R.sub.m), a series inductance (L.sub.m), a
series capacitance (C.sub.m), and a parallel capacitance (C.sub.p)
shunting the series elements. As used herein, a "resonant property"
of a microcantilever means and includes one or more elements of the
equivalent circuit model (i.e., one or more of the series
resistance, series inductance, series capacitance, and parallel
capacitance), a resonant frequency (F.sub.r, also referred to as
.omega..sub.r), a quality factor (Q), and a bandwidth (BW). The
terms "resonant property," "resonant parameter," and "resonant
characteristic" are used interchangeably herein.
In some embodiments, the damping sensor 116 (FIG. 1) is driven by a
swept frequency voltage under control of the central processing
unit 124 (FIG. 1). A numerically controlled oscillator or frequency
synthesizer performs the digital-to-analog (D/A) 120 (FIG. 1) swept
frequency drive to either the piezoelectric element 740 or the
piezoresistive element 756. The CPU 124 reads back the sensed
voltage amplitude and phase via the analog-to-digital (A/D) 120
converter to detect when the drive voltage frequency goes through
the mechanical resonant frequency of the microcantilever 700.
Accordingly, the damping sensor 116 may be driven by exciting the
piezoelectric element 740 or the piezoresistive element 756 with a
frequency synthesizer to perform a so-called frequency sweep of the
damping sensor 116. During the frequency sweep, the voltage of the
damping sensor 116 may be measured with a sense element (e.g., the
piezoresistive element 756) thereof.
From the data obtained during the frequency sweep, a quality factor
of the damping sensor 116 may be determined. For example, the
quality factor may be related to the resonant frequency,
inductance, and the series resistance (which may be proportional to
the damping) of the oscillation, according to Equation (9) below:
Q=F.sub.R/BW=R.sub.m/L.sub.m (9), wherein Q is the quality factor
of the damping sensor 116, BW is the bandwidth of the curve of
measured voltage versus frequency of the damping sensor 116 during
the frequency sweep, F.sub.r is the resonant frequency of the
damping sensor 116, R.sub.m is the series resistance of the damping
sensor 116, and L.sub.m is the series capacitance of the damping
sensor 116. In some embodiments, Q.sub.m and BW may be derived from
the curve of the measured voltage versus frequency of the damping
sensor 116 during the frequency sweep. Accordingly, F.sub.R and the
ratio of R.sub.m/L.sub.m may be determined from Q and BW. The
resonant frequency F.sub.R may be determined according to Equation
(10) below:
.times..pi..function..times. ##EQU00001## wherein L.sub.m and
C.sub.m are as defined above.
The measured resonant frequency may be compensated for temperature,
humidity (relative humidity, absolute humidity, or both), pressure,
and flowrate of the sample with data measured using data from the
environmental sensor 118 (FIG. 1). Increasing gas viscous damping
decreases the resonant frequency of the damping sensor 116. The
absolute resonant frequency of a microcantilever can drift with
time, contamination and mechanical deterioration of the
microcantilever (beam); however, the short-term stability of a
microcantilever is excellent and can be compensated for pressure,
temperature, humidity, and flowrate. To overcome drift and accuracy
issues, the resonant frequency of the damping sensor 116 may be
monitored periodically to store the historical baseline frequency
data in the memory 128, a value representative of the frequency and
viscous damping prior to detection of the exothermic trigger from
the catalytic sensor. As used herein, a baseline resonant parameter
means and includes a resonant parameter of a microcantilever (e.g.,
the damping sensor) when the microcantilever is exposed to a
reference sample (e.g., air). In some embodiments, values of the
resonant parameter may be stored in memory and may be based on data
obtained during calibration of the microcantilever (e.g., in a
factory). A shift in a resonant parameter of the microcantilever
includes a change in the resonant parameter of the microcantilever
responsive to exposure to a sample relative to the baseline
resonant parameter (e.g., the value of the resonant parameter when
the microcantilever is exposed to a reference sample).
In use and operation, responsive to a change in one or more of a
response of the catalytic sensor 112 (FIG. 1) relative to a
baseline catalytic response, a shift in a resonant parameter (e.g.,
a resonant frequency) of the damping sensor 116 (FIG. 1) (i.e., a
difference in the resonant parameter of the damping sensor 116 when
the damping sensor 116 is exposed to a sample and the resonant
parameter of the damping sensor 116 when the damping sensor 116 is
exposed to a baseline (e.g., a reference gas)), and a change in a
thermal conductivity relative to a baseline thermal conductivity,
changes in the resonant characteristics of the damping sensor 116
may be measured. A difference between the baseline resonant
frequency and each subsequent resonant frequency measurement may
correspond to changes in the damping (e.g., viscous damping) of the
sample due to varying concentration of an analyte in the sample. In
other words, the change in damping (e.g., viscous damping), which
may be measured by changes in the resonant frequency of the damping
sensor 116, may correspond to a presence of an analyte in the
sample.
Referring to FIG. 8A, the processed damping sensor 116 frequency
data and the thermal conductivity sensor 114 power data may be used
to form a two-dimensional vector of a change in TC relative to a
baseline (e.g., air) (i.e., a .DELTA.TC) versus a change in VD (a
change in resonant frequency) relative to a baseline (e.g., air),
whose magnitude is proportional to the concentration of one or more
components of the sample and whose slope is an indicator of the
composition of the sample. In other words, a presence of one or
more components (e.g., gases) in the sample may be determined based
on a ratio of a change in resonant frequency relative to the
baseline (and hence, a change in viscous damping) of the damping
sensor 116 to a change in the thermal conductivity of the sample.
The change in resonant frequency may be relative to a baseline,
such as a change relative to when the damping sensor 116 is exposed
to air compared to when the damping sensor 116 is exposed to the
sample. Similarly, the change in thermal conductivity may be
relative to a baseline, such as a change relative to when the
thermal conductivity sensor is exposed to air compared to when the
thermal conductivity sensor is exposed to the sample. Accordingly,
in some embodiments, one or more components in the sample may be
identified using the thermal conductivity sensor 114 to determine
changes in thermal conductivity and using the damping sensor 116 to
determine changes in viscous damping (or at least one of resonant
frequency, quality factor, series resistance, and bandwidth).
In addition, by subtracting the TC value measured at one point in
the ramp (e.g., at 700.degree. C.) from the value measured at
another point (e.g., at 200.degree. C.) the "slope" of a given gas'
unique TC vs. temperature relationship (e.g., mW/C) can be
determined; this slope can even serve as the "TC" value in data
analysis techniques like the one shown in FIG. 8A. Further, because
this slope tends to be relatively invariant across a wide
temperature range, this technique can aid in compensating the TC
measurement for environmental factors, especially temperature and
pressure. Such environmental factors tend to shift (or translate) a
gas' entire TC vs temperature curve upward or downward (i.e.,
affect the y-intercept of the traces on the plot), without
substantially altering the slope of each curve.
Some gases, such as helium, hydrogen and methane, have very similar
or overlapping viscous damping versus TC vectors (i.e., ratios of
viscous damping to thermal conductivity). In some embodiments,
helium and hydrogen can be differentiated by using the reaction
onset temperature (light-off temperature) determined with the
catalytic sensor 112 (FIG. 1), such as a temperature when the
magnitude of the exothermic response is greater than a
predetermined threshold value. In other words, in some such
embodiments, helium and hydrogen may be differentiated by a
temperature at which the magnitude of Exo(new) (Equation (8)) is
greater than a predetermined threshold or is a non-zero value. The
hydrogen reaction onset temperature is typically below 100.degree.
C. while the methane reaction onset temperature is typically above
400.degree. C. The exact reaction onset temperatures may vary with
the catalyst and transducer type used in the application. Helium is
non-flammable, so it is differentiated by the fact that there is no
exothermic response from the catalytic sensor 112. Utilizing
light-off temperature, or lack thereof, in this example enables
unambiguous differentiation of helium, hydrogen, and methane.
Multiple reaction onset temperatures at multiple different
temperatures indicate the presence of multiple flammable gases. The
heat of combustion, or magnitude of the response of the catalytic
sensor 112 at a reaction onset temperature, can also be used as a
gas identifier-quantifier.
In some embodiments, the presence of one or more gases in the
sample may be identified based on a ratio of one or more of a
change in at least one resonant parameter (e.g., resonant
frequency), a change in series resistance, a change in quality
factor, a change in bandwidth, a change in inductance, and a change
in parallel capacitance of the damping sensor 116 (FIG. 1) to
another of the change in the at least one resonant parameter, the
change in series resistance, the change in quality factor, the
change in bandwidth, the change in inductance, and the change in
parallel capacitance when the damping sensor 116 is exposed to the
sample compared to when it is exposed to the baseline or reference
gas. The change in the at least one resonant parameter may be
relative to a baseline of the respective resonant parameter.
In some embodiments, a composition of the gas may be determined
based on a ratio of the change in resonant frequency to a change in
one of quality factor and series resistance. FIG. 8B is a graph
showing a relationship between a change in resonant frequency to a
change in series resistance (R.sub.m) (which is proportional to
quality factor) of the damping sensor 116. In some embodiments,
different gases may exhibit a different relationship or ratio. FIG.
8C is a graph illustrating the relationship between the change in
resonant frequency to the change in series resistance of a
microcantilever when the microcantilever is exposed to different
gases.
Although the damping sensor 116 (FIG. 1) has been described as
comprising a microcantilever sensor 700 (FIG. 7A, FIG. 7B), the
disclosure is not so limited. In other embodiments, the damping
sensor 116 may include a resonant sensor such as a membrane sensor,
a quartz crystal microbalance (QCM) sensor, a surface acoustic wave
(SAW) sensor, or another resonant sensor. In addition, the at least
one resonant parameter of the damping sensor 116 may be determined
by methods such as the so-called "dashpot" method.
Although the microcantilever sensor 700 (FIG. 7A, FIG. 7B) has been
described as being configured to determine a viscous damping or a
resonant property of the sample, in some embodiments, the
microcantilever sensor 700 may be configured to measure a thermal
conductivity of the sample at one or more temperatures, a catalytic
response at one or more temperatures, a catalytic activity of the
sample at one or more temperatures, or a combination thereof. By
way of nonlimiting example, the microcantilever sensor 700 may
include a sense mechanism (e.g., sense circuitry) configured to
determine a power to maintain the microcantilever sensor 700 at a
first temperature and a second temperature such as according to
Equations (1) through (3) above. Accordingly, in some such
embodiments, the microcantilever sensor 700 may be used to
determine a thermal conductivity of the sample at the first
temperature and at least at a second temperature, and may further
be configured to determine one or more resonant characteristics
thereof. In some embodiments, the microcantilever sensor 700 may be
vibrated to increase heat transfer from the microcantilever sensor
700 to a sample proximate the microcantilever sensor 700.
Accordingly, in some embodiments, the thermal conductivity sensor
114 (FIG. 1) may comprise a microcantilever sensor 700. In some
embodiments, the microcantilever sensor 700 may include a disk or
paddle-shaped structure at an end thereof (e.g., at the free end
730). The disk or paddle-shaped structure may be configured to be
heated and transfer heat to the sample proximate the free end 730
of the microcantilever sensor 700.
In some embodiments, one or more analytes may be identified by
interacting with one or more coating materials formulated and
configured to interact with one or more specific analytes. The
coating materials may be associated with, for example, the coated
microcantilevers 115 (FIG. 1), the metal oxide semiconductor
microhotplate, or both. With reference again to FIG. 1, FIG. 7A,
and FIG. 7B, in some embodiments, the detector 100 (FIG. 1) may
further include one or more coated microcantilevers 115 (i.e.,
microcantilevers comprising a coating material). Coated
microcantilevers can also be utilized with the addition of a
coating material 764 to the free end of the microcantilever. The
one or more coated microcantilevers 115 may be substantially
similar to the microcantilever sensor 700 described above with
reference to FIG. 7A and FIG. 7B, wherein the coating material 764
comprises a selective coating material for adsorbing or otherwise
interacting with specific analytes. The coating material 764 may
include, for example, polymers, metallic, chemical, or biological
coatings with specific analyte adsorptive properties. In some
embodiments, coated microcantilevers 115 can achieve sensitivities
below the thresholds detectable by a .DELTA.TC versus .DELTA.VD
vector. Coated microcantilevers 115 may also be useful in detecting
volatile organic compounds (VOCs). In addition to the specific
examples discussed, the coated microcantilevers can provide
additional sensitivity to specific analytes. An exemplary list of
polymer microcantilever coatings include polydimethylsiloxane
(PDMS; a non-polar polymer), poly(epichlorohydrin) (PECH; a
dipolar, H-bond including polymer), poly(butyl methacrylate)
(PBMA); a dipolar, basic polymer), OV275 (a polysiloxane polymer
commercially available from Ohio Valley Specialty Company of
Marietta, OH), poly(2-dimethylaminoethyl methacrylate (PDMAEMC; a
strong basic polymer), BPS-3(a bisphenol-containing polymer), PDZ
(a polarizable phenyl), SCF101 (a hyperbranched fluoroalcohol
polycarbosilane commercially available from Seacoast Science, Inc.,
of Carlsbad, Calif.) and fluoroalcoholpolysiloxane (SXFA; an acidic
polymer), and the like. An exemplary list of metal microcantilever
coatings includes Mo, Au, Pd, and Pt, and the like. Other chemical
and biological coatings can also be utilized.
FIG. 9A and FIG. 9B illustrate a microhotplate metal oxide
semiconductor ("MOS") sensor 900 with interdigitated electrodes 930
above the resistive heater 218 (not shown in FIG. 9A for clarity),
which may be a resistive heater, and the passivation coating 220.
The MOS sensor 900 may be substantially similar to the
microhotplate sensor 200 described above with reference to FIG. 2A
and FIG. 2B, except that the MOS sensor 900 may include a MOS
coating 928 directly over electrodes 930 so that the electrical
characteristics of the MOS coating can be measured through the bond
pads 919 labeled IDE- and IDE+. The MOS coating 928 may comprise a
metal oxide (e.g., tin oxide, zinc oxide, tungsten oxide (e.g.,
WO.sub.3), a manganese oxide (e.g., MnO, MnO.sub.2,
Mn.sub.2O.sub.3), LaCoO.sub.3, LaNiO.sub.3, vanadium oxide (e.g.,
VO.sub.5), phosphorous pentoxide (e.g., P.sub.2O.sub.5), molybdenum
oxide (MoO.sub.2), cesium oxide (e.g., Cs.sub.2O), etc.), a doped
metal oxide (e.g., platinum-doped tin oxide), a polymer material
(e.g., an electrically conductive polymer material), an ionic
conductor (e.g., an electrochemical coating (also referred to as an
e-chem coating) material)), an n-type semiconductor material, a
p-type semiconductor material, a thermoelectric material, another
material, or combinations thereof. Precise temperature control is
sometimes not required by MOS microhotplates, so the kelvin
measurement points have been omitted. Temperature can be controlled
and measured by computing resistance based on the current and
voltage sourced to the heater on the I+ and I- terminals 214 shown
on FIG. 9A.
The MOS sensor 900 may be configured to interact with one or more
specific analytes of interest, such as, for example, carbon
monoxide, oxygen, hydrogen disulfide, or another gas. A resistance
as a function of temperature of the MOS sensor 900 may be measured.
The MOS response chemical sensitivity varies with temperature and
thus the temperature profile is useful as an additional chemical
differentiator. In some embodiments, a presence of one or more
analytes in the sample may be determined based on a resistance of
the MOS sensor 900 at one or more temperatures.
FIG. 10 is an overview of data collection and analysis process. Raw
data from the sensors (e.g., one or more of the thermal
conductivity sensor 114 (FIG. 1), the catalytic sensor 112 (FIG.
1), the coated microcantilever sensor 115 (FIG. 1), the damping
sensor 116 (FIG. 1), and the environmental sensors 118 (FIG. 1)) is
collected in data acquisition act 1010. Salient features from the
sensors are extracted from the raw data at act 1020. The salient
features may include, by way of nonlimiting example, a power
response of the thermal conductivity sensor 114 to exposure to the
sample at one or more temperatures, a response of the catalytic
sensor 112 to exposure to the sample at the one or more
temperatures, a response of the damping sensor 116 to exposure to
the sample, and a response of at least one of a coated
microcantilever sensor 115 and a coated microhotplate sensor 115 to
exposure to the sample. The salient features are compensated for
environmental effects of temperature, pressure humidity, and/or
flowrate at act 1030. After compensation, the data is further
processed and compared to stored data to generate the answer vector
at act 1040. The gas concentration (parts per million (ppm) or
lower explosive limit (LEL) for flammables) and the gas
identification is reported at act 1050, and then the process can be
repeated. In some embodiments, compensation for environmental
effects at act 1030 may be performed after act 1010, after act
1040, or anywhere in the process.
Although the detector 100 (FIG. 1) has been described as
determining one or more properties of a gas using specific
combinations of variables, such as the thermal conductivity at a
first temperature (e.g., a change in the thermal conductivity
relative to a baseline while the thermal conductivity sensor is at
the first temperature), the thermal conductivity at a second
temperature (e.g., a change in the thermal conductivity relative to
a baseline while the thermal conductivity sensor is at the second
temperature), the response of the catalytic sensor at the first
temperature, the catalytic activity of the catalytic sensor at the
first temperature (e.g., a change in a response of the catalytic
sensor when the catalytic sensor is at the first temperature and
exposed to the sample relative to a response of the catalytic
sensor when the catalytic sensor is at the first temperature and
exposed to the reference), the response of the catalytic sensor at
the second temperature, the catalytic activity of the catalytic
sensor at the second temperature (e.g., a change in a response of
the catalytic sensor when the catalytic sensor is at the second
temperature and exposed relative to a response of the catalytic
sensor when the catalytic sensor is at the second temperature and
exposed to the reference), the ratio of the catalytic activity at
the first temperature to the catalytic activity at the second
temperature, the exothermic response of the catalytic sensor at the
first temperature, the exothermic response of the catalytic sensor
at the second temperature, the ratio of the exothermic response at
the first temperature to the exothermic response at the second
temperature, a change in at least one resonant parameter of the
damping sensor 116, etc., the disclosure is not so limited. In some
embodiments, three or more variables may be measured and correlated
to one or more properties of a gas (e.g., identification,
concentration, etc.).
FIG. 11 is a three-dimensional plot showing .DELTA.TC vs.
.DELTA.F.sub.R vs. .DELTA.Q or .DELTA.R.sub.m (since .DELTA.Q is
proportional to .DELTA.R.sub.m). As described above, .DELTA.TC may
be determined based on the response of the thermal conductivity
sensor 114 (FIG. 1) to exposure to the sample relative to the
baseline thermal conductivity response, and .DELTA.F.sub.R and
.DELTA.Q (or .DELTA.R.sub.m) may be determined based on the
response of the damping sensor 116 (FIG. 1) to exposure to the
sample. Referring to FIG. 11, a gas may exhibit a location on the
graph with a unique direction (e.g., slope) and magnitude (i.e., a
relationship between each of .DELTA.TC, .DELTA.F.sub.R, and
.DELTA.Q (or .DELTA.R.sub.m)) and the other of the .DELTA.TC,
.DELTA.F.sub.R, and .DELTA.Q (or .DELTA.R.sub.m). For example, Gas
1, Gas 2, and Gas 3 may each include unique coordinates (i.e.,
directions) on the graph. Accordingly, gases may exhibit unique
combinations and ratios of three parameters, which may be used to
identify the composition of the gas. In some embodiments, the
values of at least three parameters may be used to determine a
composition of a sample and a concentration of gases in the sample.
Although FIG. 11 has been described as including a change in
quality factor or a change in series resistance, a change in
thermal conductivity, and a change in resonant frequency, in other
embodiments, the three parameters may include combinations of a
change in quality factor, a change in resonant frequency, a change
in thermal conductivity, a thermal conductivity at one or more
temperatures, a catalytic sensor response at one or more
temperatures, a ratio of a thermal conductivity at a first
temperature to the thermal conductivity at a second temperature, a
ratio of a catalytic response at the first temperature to the
catalytic response at the second temperature, a ratio of a
catalytic response at a given temperature to the thermal
conductivity response at the given temperature, a ratio of a
catalytic response at a temperature to the resonant frequency, a
ratio of a catalytic response at a temperature to R.sub.m, a ratio
of a resonant frequency to thermal conductivity, a ratio of a
catalytic activity at the first temperature to the catalytic
activity at the second temperature, a ratio of a catalytic activity
at a given temperature to the thermal conductivity response at the
given temperature, a ratio of a catalytic activity at a temperature
to the resonant frequency, a ratio of a catalytic activity at a
temperature to R.sub.m, a ratio of a resonant frequency to thermal
conductivity, a ratio of a reactivity at the first temperature to
the reactivity at the second temperature, a ratio of the reactivity
at a given temperature to the thermal conductivity response at the
given temperature, a ratio of a reactivity at a temperature to the
resonant frequency, a ratio of a reactivity at a temperature to
R.sub.m, and a ratio of R.sub.m to thermal conductivity.
Although FIG. 11 has been described as identifying one or more
gases in a sample with three parameters, the disclosure is not so
limited. In other embodiments, a composition of a gas may be
determined with more parameters. FIG. 12A is an illustration of how
four parameters can be visualized as six two-dimensional
projections in a multi-dimensional analysis. In other words, FIG.
12A illustrates how four individual parameters yields six distinct
pairs of parameters. The four parameters illustrated in FIG. 12A
are the ratios of: F.sub.R/TC.sub.T2, R.sub.m/TC.sub.T2,
TC.sub.T1/TC.sub.T2, and Exo.sub.T1/Exo.sub.T2, wherein TC.sub.T1
is the change in thermal conductivity at a first temperature,
TC.sub.T2 is the change in thermal conductivity of the sample at a
second temperature, Exo.sub.T1 is the reactivity at the first
temperature (determined by Equation (8) at the first temperature),
also referred to as the exothermic response at the first
temperature, and Exo.sub.T2 is the reactivity at the second
temperature (determined by Equation (8) at the second temperature),
also referred to as the exothermic response at the second
temperature. The relationship between each parameter and the sample
composition in FIG. 12A is approximately linear, and mixtures of
gases appear as linear combinations. In other words, and by way of
nonlimiting example, a mixture of 50% by volume pentane and 50% by
volume propane is located at approximately a midpoint between a
sample of 100% by volume pentane and a sample of 100% by volume
propane. Orthogonality in the projections of FIG. 12A can predict
multiple analyte identifications and concentrations. By way of
nonlimiting example, methane and ethane may exhibit similar ratios
of resonant frequency to each of series resistance, thermal
conductivity, and reactivity. However, methane and ethane may be
distinguished from each other based on at least one of a ratio of
resonant frequency to a change in the thermal conductivity at a
temperature, a ratio of change in the thermal conductivity at the
first temperature to the change in the thermal conductivity at a
second temperature, and the ratio of reactivity at the first
temperature and to the reactivity at the second temperature.
Accordingly, various combinations of variables and ratios of
variables may be used to determine a composition of a gas. The
ratios may include a ratio of resonant frequency to a change in
thermal conductivity at a temperature, a ratio of R.sub.m to a
change in the thermal conductivity at a temperature, a ratio of a
change in the thermal conductivity at a first temperature to the
change in thermal conductivity at a second temperature, a ratio of
the catalytic activity at the first temperature to the catalytic
activity at the second temperature, a ratio of the reactivity at a
first temperature to a reactivity at a second temperature, a ratio
of the ratio of the change in thermal conductivity at the first
temperature to the change in thermal conductivity at a second
temperature to the ratio of the reactivity at the first temperature
to the reactivity at the second temperature (e.g.,
((.DELTA.TCT1/.DELTA.TCT1)/(Exo.sub.T1/Exo.sub.T2))), a ratio of a
catalytic activity at a given temperature to the thermal
conductivity response at the given temperature, a ratio of a
catalytic activity at a temperature to the resonant frequency, a
ratio of a catalytic activity at a temperature to R.sub.m, a ratio
of a reactivity at a temperature to the resonant frequency, and a
ratio of a reactivity at a temperature to R.sub.m.
Accordingly, a gas may be analyzed and determined based on one or
more properties measured by one or more of the thermal conductivity
sensor 114, the catalytic sensor 112, and the damping sensor 116.
The one or more properties may include a change in thermal
conductivity at a first temperature, a change in thermal
conductivity at a second temperature, a response of the catalytic
sensor 112 at the first temperature, a response of the catalytic
sensor 112 at the second temperature, a catalytic activity at the
first temperature, a catalytic activity at the second temperature,
a reactivity (an exothermic response) at the first temperature, a
reactivity (an exothermic response) at the second temperature, a
quality factor (e.g., a quality factor shift) of the damping sensor
116 responsive to exposure to the sample, a resonant frequency
(e.g., a resonant frequency shift) of the damping sensor 116 (such
as at room temperature) responsive to exposure to the sample, a
series resistance (damping) of the damping sensor 116, a resonant
frequency of the damping sensor 116 at an elevated temperature, a
quality factor of the damping sensor 116 at an elevated
temperature, a higher-mode resonant frequency of the damping sensor
116, an equivalent circuit parameter shift of the damping sensor
116 responsive to exposure to the sample, a metal oxide
semiconductor resistance shift at the first temperature responsive
to exposure to the sample, a metal oxide semiconductor resistance
shift at the second temperature responsive to exposure to the
sample or another property, a ratio of one of the properties to at
least another of the properties, and combinations thereof.
FIG. 12B illustrates another method of determining at least one
property (e.g., an identity of at least one component) of a sample
with a so-called "radar chart" or "radar plot" using the same data
illustrated in FIG. 12A (i.e., using ratios of: F.sub.R/TC.sub.T2,
R.sub.m/TC.sub.T2, TC.sub.T1/TC.sub.T2, and Exo.sub.T1/Exo.sub.T2).
Different gases may exhibit different shapes or "fingerprints" in
the plot illustrated in FIG. 12B since one or more properties of
the gases may be different. Accordingly, an identity of one or more
gases or analytes in a sample may be determined by plotting values
of each of the parameters on the plot and recognizing the pattern
or fingerprint, such as with the central processing unit 124 (FIG.
1) or the processing subsystem 140 (FIG. 1). In some embodiments, a
concentration of one or more gases may be determined based on at
least one of a shape and size of the fingerprint (e.g., an area
within the fingerprint). In some embodiments, orthogonality in the
projections of FIG. 12B and FIG. 12C can predict multiple analyte
identifications and concentrations. By way of nonlimiting example,
methane and ethane may exhibit one or more similar properties.
However, methane and ethane may be distinguished from each other
based on a difference between one or more properties, such as one
or more of Exo.sub.T1, Exo.sub.T2, TC.sub.T1, TC.sub.T2, R.sub.m,
and F.sub.R, or ratios thereof. Accordingly, one or more properties
of the sample may be determined based on a multi-dimensional
analysis of the sample based on one or more (e.g., two more more)
sensor parameters selected from the group consisting of a change in
thermal conductivity at a first temperature, a change in thermal
conductivity at a second temperature, a change in a response of a
catalytic sensor at the first temperature relative to a baseline
(e.g., a catalytic activity at the first temperature), a change in
a response of the catalytic sensor at the second temperature
relative to a baseline (e.g., a catalytic activity at the second
temperature), a reactivity at the first temperature, a reactivity
at the second temperature, a quality factor (e.g., a quality factor
shift) of the damping sensor 116 (FIG. 1) responsive to exposure to
the sample, a resonant frequency (e.g., a resonant frequency shift)
of the damping sensor 116 (such as at room temperature) responsive
to exposure to the sample, a series resistance (damping) of the
damping sensor 116, a resonant frequency of the damping sensor 116
at an elevated temperature, a quality factor of the damping sensor
116 at an elevated temperature, a higher-mode resonant frequency of
the damping sensor 116, an equivalent circuit parameter shift of
the damping sensor 116 to exposure to the sample, a metal oxide
semiconductor resistance shift at the first temperature responsive
to exposure to the sample, a metal oxide semiconductor resistance
shift at the second temperature responsive to exposure to the
sample or another property. In some embodiments, the one or more
properties of the sample may be determined based on a relationship
between each of the sensor parameters of the set of sensor
parameters with each of the other sensor parameters of the set of
sensor parameters.
Although FIG. 12B illustrates the radar plot as including six
variables, the disclosure is not so limited. In other embodiments,
the radar plot may include fewer or more variables. By way of
nonlimiting example, the radar plot may include three variables,
four variables, or five variables. In other embodiments, the radar
plot may include more than six variables, such as seven, eight,
nine, ten, etc., variables. FIG. 12C and FIG. 12D illustrate
another method of determining at least one property of a sample.
Referring to FIG. 12C, a composition of a sample may be determined
based on a combination of responses from a combination of sensors.
By way of nonlimiting example, the detector 100 (FIG. 1) may
include a catalytic sensor comprising a molybdenum catalyst, a
catalytic sensor comprising a gold catalyst, a catalytic sensor
comprising a palladium catalyst, a catalytic sensor comprising a
platinum catalyst, a thermal conductivity sensor, a damping sensor,
a coated microcantilever sensor comprising a first polymer, a
coated microcantilever sensor comprising a second polymer, a coated
microcantilever sensor comprising a third polymer, a coated
microcantilever sensor comprising a BPS-3 polymer, a coated
microcantilever sensor comprising a coating configured to interact
with an acid, a coated microcantilever sensor comprising a coating
configured to interact with hydrogen bonds, a coated
microcantilever comprising a coating configured to interact with a
phenyl group, a coated microcantilever comprising a coating
configured to interact with a basic gas, a MOS sensor comprising a
coating configured to interact with carbon monoxide, a MOS sensor
comprising a coating formulated to interact with carbon dioxide, a
MOS sensor comprising a coating formulated to interact with
hydrogen sulfide. A magnitude of a response (or a change in a
response relative to a baseline response) from each of the sensors
responsive to exposure to the sample may be measured. The responses
may be graphed to determine a composition of the sample. By way of
nonlimiting example, each gas or analyte of interest may exhibit a
different so-called "fingerprint." In some embodiments, a
concentration of different analytes in the sample may be determined
based on a size of the fingerprint. The composition of the sample
may be determined by comparing the responses from each sensor to
values stored in a look-up table, by pattern recognition
techniques, or a combination thereof.
FIG. 12D is a time sequence showing how the radar plots
(fingerprints) may change responsive to samples exiting a
concentrator or separator, each sample with different compositions
in the time sequence. A concentrator may contain a sorbent material
that accumulates one or more analytes over time. When the sorbent
material is heated, the analytes may be desorbed. Different
analytes desorb at different temperatures, and therefore, at
different times when the temperature is ramped over time. In some
embodiments, the detector 100 (FIG. 1) may include a separator 110
(FIG. 1) positioned such that the sample is exposed to the
separator 110 prior to the sensors. By way of nonlimiting example,
the separator 110 may be located proximate the sensors (e.g., at a
location such that the sample passes through the separator prior to
being exposed to the thermal conductivity sensor, the catalytic
sensor, and the damping sensor). The separator 110 may include a
gas chromatograph (GC) or column that has different transit times
for various gas analytes, hence yielding different analytes exiting
the column at different times. The separator 110 may be configured
to separate different components of the sample such that the
sensors (e.g., the thermal conductivity sensor, the catalytic
sensor, and the damping sensor) are exposed to different components
of the sample at different times. Accordingly, different components
(e.g., gases) of the sample may elute through the separator at
different times, facilitating identification of more than one
analyte in the sample. In some such embodiments, the processing
subsystem may be configured to generate a different fingerprint for
each component in the sample based on the time at which the
particular component elutes through the separator.
FIG. 13 is a simplified flow diagram illustrating a method 1300 of
determining one or more properties of a gas sample. The method 1300
includes act 1302 including exposing one or more sensors of a
detector to a sample including one or more analytes of interest;
act 1304 including measuring a thermal conductivity of the sample
while a thermal conductivity sensor is at a first temperature and
while the thermal conductivity sensor is at a second temperature;
act 1306 including measuring a response of a catalytic sensor at
the first temperature and at the second temperature; act 1308
including determining one or more properties of a damping sensor
responsive to exposure to the sample; act 1310 including
determining one or more properties of at least one of a coated
microcantilever sensor and a MOS sensor; act 1312 including
compensating responses received in acts 1304 through 1310 for one
or more of temperature, pressure, relative humidity, absolute
humidity, and flowrate; act 1314 including determining one or more
properties of the sample based on the information obtained in acts
1302 through 1312; act 1316 including determining a presence (e.g.,
an identity) of one or more gases in the sample; and act 1318
including determining a concentration of the one or more gases in
the sample.
Act 1302 may include exposing one or more sensors of the detector
to a sample including one or more analytes of interest. In some
embodiments, the detector may include at least a thermal
conductivity sensor, a catalytic sensor, and a damping sensor. In
some embodiments, the detector may further include at least one of
a coated microcantilever sensor and a MOS sensor.
Act 1304 may include measuring a thermal conductivity of the sample
while a thermal conductivity sensor is at a first temperature and a
second temperature responsive to exposure to a sample. The thermal
conductivity at each of the first temperature and the second
temperature may be determined according to the method 400 described
above with reference to FIG. 4. In some embodiments, the change in
the thermal conductivity of the sample when the thermal
conductivity sensor is at each of the first temperature and the
second temperature relative to a baseline thermal conductivity at
each of the respective first temperature and second temperature may
be determined. In other words, in some embodiments, a value of
.DELTA.TC (Equation (3)) may be determined at each of the first
temperature and the second temperature.
Act 1306 may include measuring a response of the catalytic sensor
at the first temperature and at the second temperature to exposure
to the sample. In some embodiments, act 1306 may be performed
substantially simultaneously with act 1304. The response of the
catalytic sensor at the first temperature and at the second
temperature may be determined as described above with reference to
the method 600 described above with reference to FIG. 6. In some
embodiments, act 1306 may include determining a catalytic activity
(i.e., Delta Cat (Equation (7))) at each of the first temperature
and the second temperature.
Act 1308 may include determining one or more properties of a
damping sensor responsive to exposure to the sample. In some
embodiments, act 1308 may be performed substantially simultaneously
with acts 1304 and 1306. The one or more properties may be selected
from the group consisting of a resonant frequency, a series
resistance, a series inductance, a series capacitance, a parallel
capacitance, a quality factor, and a bandwidth of the damping
sensor. The one or more properties may be determined as described
above with reference to FIG. 8A and FIG. 8B and Equation (9) and
Equation (10).
Act 1310 may include determining one or more properties of the at
least one of a coated microcantilever sensor and a metal oxide
semiconductor sensor, which may be measured, such as a resistance
of the sensor as a function of temperature or a change in at least
one resonant parameter of the coated microcantilever sensor. The at
least one of the coated microcantilever sensor and the metal oxide
semiconductor sensor may be exposed to the sample. The resistance
may be an indication of interaction of the at least one of a metal
oxide semiconductor sensor with one or more analytes in the sample.
A change in the at least one resonant parameter of the coated
microcantilever sensor may be an indication of interaction of the
coated microcantilever sensor with one or more analytes in the
sample.
Act 1312 may include compensating responses received in acts 1304
through 1310 for one or more of temperature, pressure, relative
humidity, absolute humidity, and flowrate. The compensation may be
based on the temperature, pressure, relative humidity, absolute
humidity, and/or flowrate of the sample measured with, for example,
the one or more environmental sensors 118 (FIG. 1).
Act 1314 may include determining one or more properties of the
sample based on the information obtained in acts 1304 through 1312.
The one or more properties may include, by way of nonlimiting
example, a change in thermal conductivity of the sample when the
thermal conductivity sensor is at the first temperature responsive
to exposure to the sample relative to a baseline thermal
conductivity at the first temperature, the change in thermal
conductivity of the sample when the thermal conductivity sensor is
at the second temperature responsive to exposure to the sample
relative to the baseline thermal conductivity at the second
temperature, a catalytic response of the catalytic sensor when the
catalytic sensor is at the first temperature, a catalytic response
of the catalytic sensor when the catalytic sensor is at the second
temperature, a catalytic activity of the catalytic sensor when the
catalytic sensor is at the first temperature, the catalytic
activity of the catalytic sensor when the catalytic sensor is at
the second temperature, an exothermic response at the first
temperature, an exothermic response at the second temperature, the
change in resonant frequency of the damping sensor, the change in
bandwidth or quality factor of the damping sensor, a resistance of
the MOS sensor at one or more temperatures, or another
property.
Act 1316 may include determining an identity (e.g., a presence) of
one or more gases in the sample. The presence of the one or more
gases may be determined based on any of the methods described
herein. In some embodiments, the identity of one or more gases in
the sample may be determined based on one or more of a ratio of the
change in thermal conductivity at a first temperature to the change
in thermal conductivity at a second temperature, the ratio of the
change in reactivity at the first temperature to the change in
reactivity at the second temperature, the ratio of the catalytic
activity at the first temperature to the catalytic activity at the
second temperature, the ratio of the change in thermal conductivity
at a temperature to the change in reactivity at the same
temperature, the ratio of quality factor of a damping sensor
exposed to the sample to the change in thermal conductivity, the
ratio of the quality factor to the resonant frequency, the ratio of
the ratio of change in thermal conductivity at two temperatures to
the ratio of change in reactivity at the two temperatures (i.e.,
(TC.sub.T1/TC.sub.T2)/(Exo.sub.T1/Exo.sub.T2), or combinations
thereof.
Act 1318 may include determining a concentration of the one or more
gases in the sample. The concentration of the one or more gases may
be determined based on any of the methods described herein.
Although FIG. 13 is illustrated as including a particular order,
the disclosure is not so limited. In some embodiments, a method of
determining one or more properties of a gas may not include all of
the acts illustrated and described with reference to FIG. 13. In
some embodiments, the acts 1302 through 1318 may be performed in
any order.
A simplified process flowchart according to one embodiment suitable
for identification of one or more flammable gases is illustrated in
FIG. 14. At act 1410, the catalytic sensor and the thermal
conductivity sensor are utilized to determine if an exothermic gas
is present. Act 1465 includes updating baseline data if a presence
of an exothermic gas is not detected. A presence of an exothermic
gas may be detected responsive to a non-zero value of Exo(new)
(e.g., an Exo(new) value having a magnitude greater than a
predetermined threshold) according to Equation (8) above. If no
reaction onset is detected, the baseline data for the catalytic
sensor and the thermal conductivity sensor is updated. If an
exothermic gas is detected, the last stored baseline is used as the
baseline values at act 1415 and the process can be repeated without
baseline updates until the exothermic reaction is no longer
detected. The measured results are compensated for the
environmental effects of temperature, pressure, humidity (relative
humidity, absolute humidity, or both), and flowrate at act
1420.
The slope of the vector delta power (proportional to TC change)
versus the delta frequency (proportional to viscous damping or
density change) is computed at 1460. Stated another way, act 1460
includes determining a ratio of the change in Delta TC, according
to Equation (4) above, to the change in resonant frequency of the
damping sensor. The slope, and hence, the ratio, may be used to
determine the gas ID and appropriate calibration at act 1455 to be
used in subsequent processing. The calibration may be determined in
a laboratory and may be used to determine a concentration of the
identified gas based on the calibration value and the magnitude of
the Delta TC value and the resonant frequency value. Once the
calibration data is applied, the magnitude of the delta power
versus delta frequency vector can be used to determine the gas
concentration at act 1440, sometimes expressed as percent lower
explosive limit (LEL) for flammable gases, but also expressed as
parts per million (ppm) if the gas' identity is determined and the
relationship between % LEL and ppm is known. The magnitude may be
determined based on Equation (11) below:
Magnitude=(VD.sup.2+TC.sup.2).sup.1/2 (11), wherein VD is the
viscous damping and TC is the thermal conductivity.
Note that, in some embodiments, the gas concentration cannot be
accurately quantified without first identifying the gas so that the
appropriate calibration can be applied, as the magnitude varies
with gas type.
Further gas data differentiation analysis utilizes the TC data
collected at multiple temperatures from the thermal conductivity
sensor at act 1445. The TC for various gases increases with
increasing temperature. Since the rate and magnitude of the TC
increase with temperature are unique by gas type, the magnitude and
slope of the TC versus temperature vector can be utilized in the
analysis as an additional gas concentration and identity
discriminator.
At the completion of the analysis, results are reported and the
processed data can be used to update compensation and calibration
data at act 1450. For instance, the magnitude of the catalytic
sensor response can be compared to the magnitude of the delta power
versus delta frequency vector. If the catalytic response has
diminished due to poisoning or aging, the appropriate compensation
can be applied to the catalytic response. If the response of the
catalytic sensor cannot be compensated or calibrated for within
preset limits, or has degraded below an acceptable threshold of
performance, a fault is reported.
FIG. 15A is a simplified flow diagram of another embodiment of
determining one or more properties of a sample, in accordance with
embodiments of the disclosure and is suitable in both flammable and
non-flammable gas detection and identification applications. The
method includes determining whether there is a shift (e.g., a
change) in thermal conductivity of the sample relative to a
baseline thermal conductivity (i.e., whether a value of .DELTA.TC
is greater than a predetermined number or is a non-zero value) at
act 1502. If there is no change in thermal conductivity of the
sample at act 1502, the method includes updating baseline values,
as necessary, received from one or more sensors at act 1504. Act
1506 includes establishing a thermal conductivity of the sample at
a first temperature (i.e., when the thermal conductivity sensor is
at the first temperature) and the thermal conductivity of the
sample at the second temperature (i.e., when the thermal
conductivity sensor is at the second temperature). Act 1508 may
include performing environmental compensation for at least one of
temperature, pressure, relative humidity, absolute humidity, and
flowrate. Act 1512 may include determining a slope, a direction, or
both of a vector of the thermal conductivity at the first
temperature to the thermal conductivity at the second temperature.
In some embodiments, determining the slope of the vector may
include determining a ratio of the thermal conductivity of the
sample at the first temperature (e.g., a response of the sensor at
the first temperature) to the thermal conductivity of the sample at
the second temperature (e.g., a response of the sensor at the
second temperature). Act 1514 may include comparing a slope, a
direction, or both of the vector to values stored in a database
(e.g., memory) to determine an identity of one or more gases in the
sample and to select appropriate calibration data (e.g., a
k-factor). Act 1516 may include determining a concentration (C)
(such as a percent lower explosive limit (% LEL) or ppm) of one or
more gases according to Equation (5) above. In some embodiments,
the concentration may be determined based on the thermal
conductivity at a single temperature. In some such embodiments, the
concentration may be determined based on Equation (12) below:
C=k(TC.sub.T1) (12), Act 1518 may include reporting results to the
processor, and updating compensation and calibration data in the
database.
FIG. 15B is a simplified flow diagram of another embodiment of
determining at least one property of a sample that does not utilize
a catalytic sensor (i.e., the catalytic sensor 112) and thus is
suitable for use in both flammable and non-flammable gas detection
and identification applications. In FIG. 15B, reference numerals
may correspond to the reference numerals of FIG. 14, except that
the reference numerals begin with "15" rather than "14."
Accordingly, reference numeral 1520, 1560, 1555, 1540, 1545, 1550,
1565 may correspond to reference numerals 1420, 1460, 1455, 1440,
1445, 1450, and 1465, respectively. In this embodiment, the
resonant frequency of a damping sensor and the thermal conductivity
sensor are monitored to detect a shift in VD or TC at act 1510
(.DELTA.VD or .DELTA.TC). If a shift is VD or TC is not detected in
act 1510, the baseline values for TC and VD are updated at act 1565
and act 1510 is repeated. Subsequent processing at act 1515 is
initiated when a shift from the baseline data is detected. Other
sensors, such as MOS and coated microcantilever sensors, could also
be used in the processing to provide added gas type selectivity, as
illustrated in FIG. 16.
FIG. 16 shows a process flow diagram that utilizes aspects of the
present disclosure. One should appreciate that the exact ordering
of the processes could be altered, and some processes shown
operating in parallel could be executed sequentially. To best
appreciate the processing potential illustrated by FIG. 16,
consider its operation with the following gases: helium (He),
Hydrogen (H.sub.2), Methane (CH.sub.4), hydrogen sulfide
(H.sub.2S), carbon monoxide (CO) and carbon dioxide (CO.sub.2).
The method may include act 1612, including reading the sensors
(e.g., the catalytic sensor, the thermal conductivity sensor, the
damping sensor, the MOS sensor, the coated microcantilever sensor,
etc.) and compensating them for the environmental effects of
temperature, pressure, relative humidity, absolute humidity, and a
flowrate of the sample. Helium, hydrogen, and methane have similar
TC and VD properties making them hard to distinguish using these
properties alone. Helium is non-flammable, so an exothermic
reaction (e.g., an exothermic event) would not be detected at act
1614. Depending on the mix of MOS and coated microcantilevers used
at act 1634, helium may or may not have a cross sensitivity, in
this example it is assumed there is no cross sensitivity to the MOS
or coated microcantilevers, and processing would proceed to check
for a .DELTA.TC or .DELTA.VD change at act 1648. Helium would
trigger a detected change in both .DELTA.TC and .DELTA.VD, thus it
would be classified as a non-flammable without cross sensitivity at
act 1650 and processing would proceed to establishing baseline
responses for TC and VD while also determining the slope of the TC
versus VD vector at act 1620. Helium would next be identified by
its slope from a stored list of slopes for non-flammables without
cross sensitivities at act 1652. With helium being properly
identified, the concentration can now be determined using
calibration data and the magnitude of the TC versus VD vector at
act 1624. The magnitude of the TC versus VD vector may be
proportional to the gas concentration, but varies by the gas type,
hence it is necessary to apply calibration data unique to the gas
identification to determine the proper concentration. At this point
in the process, helium has been differentiated from hydrogen and
methane and has been properly identified and quantified.
The TC versus temperature is also unique by gas type and can be
further utilized to refine the analysis results, and as a system
validation/confidence check of overall sensor performance or fault
detection at act 1628. Data from all the sensors can be compared at
act 1630 in a multi-dimensional analysis. An example of such a
multi-dimensional "fingerprint" analysis is illustrated in FIG. 12B
and FIG. 12C. FIG. 12D illustrates how this analysis can be applied
in a time sequence when a separator 110 (FIG. 1) or gas
chromatograph is used ahead of (proximate) the system sensors.
Results are reported, compensation values are updated, calibration
values are updated, and any faults detected are reported in act
1632. The processing then repeats without updating the baseline
data value. If no gas was detected by an exothermic event at act
1614, .DELTA.TC or .DELTA.VD at acts 1636 or 1648, then the
baseline data is updated before repeating the process.
Next consider the flow with H.sub.2 or CH.sub.4, both flammable
gases with similar .DELTA.TC versus .DELTA.VD vectors. An
exothermic reaction (event) (such as a reactivity or an exothermic
response, as determined by an Exo(new) value greater than a
predetermined threshold) at act 1614 would be detected and the
reaction onset (light-off) temperature and magnitude of the
exothermic reaction (event) would be saved at act 1616. In the
event that a MOS or coated microcantilever response was also
detected, the flammable detection at act 1618 information is shared
with the MOS/coated microcantilever processing at act 1638 so
appropriate sensor cross sensitivity can be analyzed. The .DELTA.TC
versus .DELTA.VD vector compared to the baseline values is
determined at act 1620 and the flammable gas is identified by the
vector slope and reaction onset (light-off) temperature at act
1622. H.sub.2 is differentiated from CH.sub.4 by its lower reaction
onset (light-off) temperature. The gas being properly identified,
the appropriate .DELTA.TC versus .DELTA.VD magnitude calibration
data is applied to determine the gas concentration at act 1626. The
remaining processing is the same as previously described for He,
and the process is repeated without updating the baseline values
until an exothermic event is no longer detected. If multiple
flammable gases were present, multiple light-off temperatures would
be observed and can be used to identify the individual gas
components. With reference again to FIG. 3C, multiple gases in the
sample may be determined based on the ratio of the thermal
conductivity at the first temperature and the thermal conductivity
at the second temperature. A concentration thereof may be
determined based on the k-factor. In some embodiments, mixtures of
gases may exhibit a ratio depending on a composition of the
mixture. By way of example only, a mixture including 50% hexane and
50% hydrogen may have a ratio of thermal conductivity at the first
temperature to the thermal conductivity at the second temperature
equal to about the average ratio for the individual components.
The next gas in the list to consider is H.sub.2S. In some
embodiments, H.sub.2S MOS sensors can detect H.sub.2S at
concentrations much lower than can be detected by .DELTA.TC or
.DELTA.VD. In this case, H.sub.2S would be detected by the H.sub.2S
MOS sensor at act 1634, but not detected by with a .DELTA.TC or
.DELTA.VD shift at act 1636. Processing would proceed to identify
the gas as having a MOS response with a .DELTA.TC or .DELTA.VD
similar to air or, in the case of H.sub.2S, a .DELTA.TC or
.DELTA.VD may be too small to detect at act 1644. The gas would be
identified as H.sub.2S at act 1646 and the processing would proceed
to the multi-dimensional analysis at act 1630. After the results
are reported at act 1632, the baselines would be updated at act
1642 since no .DELTA.TC or .DELTA.VD shift was detected. The whole
process would then repeat.
Carbon monoxide (CO) is a gas that is also readily detectable with
a MOS sensor. The CO .DELTA.TC and .DELTA.VD shift is similar to
that of a standard air composition, and hence would not produce a
significant .DELTA.TC or .DELTA.VD shift. In the case of both
H.sub.2S and CO, the multi-dimensional analysis at act 1630 is
useful in properly identifying and quantifying gases absent a
.DELTA.TC or .DELTA.VD shift.
Carbon dioxide (CO.sub.2) is a gas that is not readily detected by
a MOS sensor. Being non-flammable, it would not be detected by an
exothermic event at act 1614, nor would it be detected by a MOS
sensor at act 1634. CO.sub.2 would produce a .DELTA.TC or .DELTA.VD
shift at act 1648, and would be identified from the non-flammable
without a MOS response list at act 1650 by the .DELTA.TC versus
.DELTA.VD vector slope at act 1620. The concentration would be
determined from the .DELTA.TC versus .DELTA.VD magnitude with the
appropriate calibration data applied at act 1624. Processing would
proceed as in previous examples. The MOS and coated
microcantilevers can also be used to parse the identification of
any TC versus VD vector ambiguities by analyzing cross
sensitivities at act 1640 prior to selection of the magnitude
calibration selection at act 1624.
The multi-dimensional analysis that combines the responses at act
1630 and as illustrated in FIG. 12B and FIG. 12C can identify and
quantify a plurality of gases and volatile organic compounds (VOCs)
at very low concentration levels.
FIG. 17 is a flow diagram illustrating a method of determining one
or more properties of a sample, according to some embodiments of
the disclosure. Method 1700 may include act 1710 including
performing a frequency sweep of a piezoelectric element of a
microcantilever sensor (e.g., a damping sensor 116 (FIG. 1))
without a coating (or with a substantially inert coating) and
measuring an amplitude response and resonant frequency of the inert
microcantilever sensor. The microcantilever sensor is driven by a
swept frequency voltage under control of the central processing
unit (CPU) 124 (FIG. 1). A numerically controlled oscillator or
frequency synthesizer performs the digital-to-analog (D/A)
converter 120 (FIG. 1) swept frequency drive to either the
piezoelectric or piezoresistive element. The CPU 124 reads back the
sensed voltage amplitude and phase via the analog-to-digital (A/D)
converter 120 to detect when the drive voltage frequency goes
through the mechanical resonant frequency of the microcantilever.
One or more of the inductance, series capacitance, parallel
capacitance, series resistance, resonant frequency, quality factor,
and bandwidth of the microcantilever sensor may be determined from
the data obtained during the frequency sweep using, for example, an
equivalent circuit model, as described above with reference to
Equation (9) and Equation (10).
Act 1720 may include exposing a reference microhotplate sensor
(e.g., thermal conductivity sensor 112 (FIG. 1)) and a catalytic
microhotplate sensor (e.g., catalytic sensor 112 (FIG. 1)) to a
reference (e.g., air) and ramping a temperature thereof. The power,
resistance, voltage, and current to each of the reference
microhotplate sensor (e.g., thermal conductivity sensor) and the
catalytic microhotplate sensor may be measured at each temperature,
as described above with reference to Equations (1) through (3),
(7), and (8). Act 1730 may include storing the sensor responses and
calibration data in a database. At act 1730, the database stores
the sensor responses, training data, and calibration data used in
the analysis.
Act 1740 includes re-ramping the temperature of the thermal
conductivity sensor and the catalytic microhotplate sensor and
determining each of .DELTA.TC, Delta Cat, and Exo(new) according to
Equations (3), (7), and (8), respectively, described above. If the
power in the resultant exothermic signal, Exo(new) deviates from
its nominal value, an exothermic reaction is detected at act 1750,
hereinafter referred to as a light-off event. The temperature of
the light-off is another identifier of the gas type detected.
Multiple light-offs at differing temperatures is an indication of
multiple flammable gases present in the sample. Accordingly, act
1750 includes determining one or more temperatures where Exo(new)
deviates from its nominal value (e.g., zero). The one or more
temperatures where Exo(new) deviates from a nominal value may be
used to identify a presence of one or more gases in the sample.
Act 1760 may include exposing a MOS sensor to the sample. The MOS
sensor data includes the conductivity versus temperature and the
MOS electrochemical measurements that are used in the analysis.
The measured resonant frequency can be compensated for temperature,
humidity and pressure conditions with data measured by
environmental sensor 118. Act 1770 may include compensating one or
more of the resonant frequency, the response of the thermal
conductivity microcantilever, and the response of the catalytic
microcantilever for one or more of temperature, relative humidity,
absolute humidity, and pressure.
Act 1780 may include analyzing the data received from each of the
sensors. The analysis may include calibrating sensors using the
data in the database. Act 1780 may include determining one or more
properties of the sample based on the responses of the sensors
responsive to exposure to the sample.
Additional nonlimiting example embodiments of the disclosure are
set forth below.
Embodiment 1
A system for detecting, identifying and quantifying gases, the
system comprising: a microhotplate sensor that senses the gas'
thermal conductivity; a microcantilever probe sensor that senses
the gas' viscous damping; and a subsystem that measures,
compensates and analyzes thermal conductivity versus viscous
damping vector compared to stored baseline responses, determines
the gas identification from the resultant vector slope, and
determines the gas concentration from the resultant vector
magnitude calibrated to the specific gas identification.
Embodiment 2
A system for detecting, identifying and quantifying flammable
gases, the system comprising: a microhotplate catalytic sensor that
detects a gas' exothermic reaction and light-off temperature(s); a
microhotplate reference sensor that senses the gas' thermal
conductivity and is also used to compensate the catalytic sensor; a
microcantilever probe sensor that senses viscous damping; and a
subsystem that utilizes detection of an exothermic reaction to
trigger additional processing, and measures, compensates and
analyzes thermal conductivity versus viscous damping vector
relative to stored baseline responses, wherein the thermal
conductivity, viscous damping, and light-off temperature data are
analyzed to determine the flammable gas' identification, and
wherein the gas' concentration is determined from the resultant
vector magnitude calibrated based upon the gas identification.
Embodiment 3
A system for detecting, identifying and quantifying gases, the
system comprising: a microhotplate catalytic sensor that detects a
gas' exothermic reaction and light-off temperature(s); a
microhotplate reference sensor that senses the gas' thermal
conductivity and is also used to compensate the catalytic sensor; a
microcantilever probe sensor that senses viscous damping; a
plurality of microhotplate MOS sensors; and a subsystem that parses
flammable from non-flammable gases, measures, compensates and
analyzes thermal conductivity versus viscous damping vector
relative to stored baseline responses, identifies flammable gases
by light-off temperature and the slope of thermal conductivity
versus viscous damping vector, identifies non-flammable gases by
the slope of thermal conductivity versus viscous damping vector,
utilizes the MOS sensor responses to parse gas identification
ambiguities to identify and to quantify gases that are not
detectable with a thermal conductivity versus viscous damping
vector, and quantifies gases having detected changes in thermal
conductivity and viscous damping by applying a stored gas specific
calibration to the magnitude of the thermal conductivity versus
viscous damping vector.
Embodiment 4
A system for detecting, identifying and quantifying gases, the
system comprising: a microhotplate catalytic sensor that detects a
gas' exothermic reaction and light-off temperature(s); a
microhotplate reference sensor that senses the gas' thermal
conductivity and is used to compensate the catalytic sensor; a
microcantilever probe sensor that senses viscous damping; a
plurality of microhotplate MOS sensors; a plurality of coated
microcantilever sensors; and a subsystem that parses flammable from
non-flammable gases, measures, compensates and analyzes thermal
conductivity versus viscous damping vector compared to stored
baseline responses, identifies flammable gases by light-off
temperature, the slope of thermal conductivity versus viscous
damping vector, identifies non-flammable gases by the slope of
thermal conductivity versus viscous damping vector, utilizes the
MOS sensor responses and coated microcantilever responses to parse
gas identification ambiguities and to identify and quantify gases
that are not detectable with a thermal conductivity versus viscous
damping vector, and quantifies gases having detected changes in
thermal conductivity and viscous damping by applying a stored gas
specific calibration to the magnitude of the thermal conductivity
versus viscous damping vector.
Embodiment 5
A system for detecting, identifying, and quantifying gases, the
system comprising: a microhotplate sensor that senses the gas'
thermal conductivity; a microcantilever probe sensor that senses
the gas' viscous damping; and a subsystem that measures,
compensates and analyzes thermal conductivity versus viscous
damping vector compared to stored baseline responses, determines
the gas identification from the resultant vector slope, and
determines the gas concentration from the resultant vector
magnitude calibrated to the specific gas identification.
Embodiment 6
A system for detecting, identifying and quantifying flammable
gases, the system comprising: a microhotplate catalytic sensor that
detects a gas' exothermic reaction and light-off temperature(s); a
microhotplate reference sensor that senses the gas' thermal
conductivity and is also used to compensate the catalytic sensor; a
microcantilever probe sensor that senses viscous damping; and a
subsystem that utilizes detection of an exothermic reaction to
trigger additional processing, and measures, compensates and
analyzes thermal conductivity versus viscous damping vector
relative to stored baseline responses, wherein the thermal
conductivity, viscous damping, and light-off temperature data are
analyzed to determine the flammable gas' identification, and
wherein the gas' concentration is determined from the resultant
vector magnitude calibrated based upon the gas identification.
Embodiment 7
A system for detecting, identifying and quantifying gases, the
system comprising: a microhotplate catalytic sensor that detects a
gas' exothermic reaction and light-off temperature(s); a
microhotplate reference sensor that senses the gas' thermal
conductivity and is also used to compensate the catalytic sensor; a
microcantilever probe sensor that senses viscous damping; a
plurality of microhotplate MOS sensors; and a subsystem that parses
flammable from non-flammable gases, measures, compensates and
analyzes thermal conductivity versus viscous damping vector
relative to stored baseline responses, identifies flammable gases
by light-off temperature and the slope of thermal conductivity
versus viscous damping vector, identifies non-flammable gases by
the slope of thermal conductivity versus viscous damping vector,
utilizes the MOS sensor responses to parse gas identification
ambiguities to identify and to quantify gases that are not
detectable with a thermal conductivity versus viscous damping
vector, and quantifies gases having detected changes in thermal
conductivity and viscous damping by applying a stored gas specific
calibration to the magnitude of the thermal conductivity versus
viscous damping vector.
Embodiment 8
A system for detecting, identifying and quantifying gases, the
system comprising: a microhotplate catalytic sensor that detects a
gas' exothermic reaction and light-off temperature(s); a
microhotplate reference sensor that senses the gas' thermal
conductivity and is used to compensate the catalytic sensor; a
microcantilever probe sensor that senses viscous damping; a
plurality of microhotplate MOS sensors; a plurality of coated
microcantilever sensors; and a subsystem that parses flammable from
non-flammable gases, measures, compensates and analyzes thermal
conductivity versus viscous damping vector compared to stored
baseline responses, identifies flammable gases by light-off
temperature, the slope of thermal conductivity versus viscous
damping vector, identifies non-flammable gases by the slope of
thermal conductivity versus viscous damping vector, utilizes the
MOS sensor responses and coated microcantilever responses to parse
gas identification ambiguities and to identify and quantify gases
that are not detectable with a thermal conductivity versus viscous
damping vector, and quantifies gases having detected changes in
thermal conductivity and viscous damping by applying a stored gas
specific calibration to the magnitude of the thermal conductivity
versus viscous damping vector.
Embodiment 9
The system of any one of Embodiments 1 through 8 that further
measures the thermal conductivity at multiple temperatures and
utilizes the resultant thermal conductivity versus temperature
vector as an additional measure of the gas concentration and
identification.
Embodiment 10
The system of any one of Embodiments 1 through 8, wherein the gas'
thermal conductivity is measured at a temperature greater than an
ambient temperature.
Embodiment 11
The system of any one of Embodiments 1 through 8, that parses gases
by those that are less dense than air and those that are denser
than air.
Embodiment 12
The system of any one of Embodiments 1 through 8, further
comprising a temperature sensor that is used to compensate the
microhotplate and microcantilever sensor measurements for
temperature variations.
Embodiment 13
The system of any one of Embodiments 1 through 8, further
comprising a humidity sensor that is used to compensate the
microhotplate and microcantilever sensor measurements for humidity
variations.
Embodiment 14
The system of any one of Embodiments 1 through 8, further
comprising a pressure sensor that is used to compensate the
microhotplate and microcantilever sensor measurements for pressure
variations.
Embodiment 15
The system of any one of Embodiments 1 through 8, wherein the
reference sensor response is subtracted from the catalytic sensor
response to compensate the catalytic sensor for temperature,
pressure, humidity, and flow variations.
Embodiment 16
The system of any one of Embodiments 1 through 8, wherein a
baseline response from each of the sensors is stored prior to
detection of a gas and subsequently subtracted from each sensors'
response to produce a delta response that is used in further
analysis.
Embodiment 17
The system of any one of Embodiments 1 through 8, further
comprising a filter that selectively restricts gas flow to the
microhotplates from the external gas environment.
Embodiment 18
The system of any one of Embodiments 1 through 8, further
comprising a flame arrestor between the microhotplates and the
external gas environment.
Embodiment 19
The system of any one of Embodiments 1 through 8, wherein the
quality factor of the microcantilever is derived and used to parse
the individual contributions of viscous damping components of
density and viscosity, wherein the combined analysis of density,
viscosity, and thermal conductivity are utilized to identify gas
component identification and its concentration.
Embodiment 20
The system of any one of Embodiments 2 through 4 or 6 through 8,
wherein the measured responses from the microhotplate reference
sensor, the microhotplate catalytic sensor and the microcantilever
sensor responses are compared with each other to compensate for
sensor drift and to detect malfunctions.
Embodiment 21
The system of any one of Embodiments 1 through 8, wherein the
circuitry is operated at reduced power between measurements.
Embodiment 22
The system of any one of Embodiments 1 through 8, wherein
calibration data for the sensors is stored in a non-volatile memory
and used to calibrate the sensor measurements.
Embodiment 23
The system of any one of Embodiments 1 through 8, wherein
calibration data for quantifying the gas concentration is stored in
non-volatile memory and selected based on the gas identity.
Embodiment 24
The system of any one of Embodiments 1 through 8, wherein sensor
response profiles for different gases are stored in a non-volatile
memory.
Embodiment 25
The system of any one of Embodiments 1 through 8, wherein the
microcantilever vibration is driven and sensed with a single
piezoelectric element.
Embodiment 26
The system of any one of Embodiments 1 through 8, wherein the
microcantilever vibration is driven with a piezoelectric element
and sensed with a piezoresistive element.
Embodiment 27
The system of any one of Embodiments 1 through 8, wherein a
piezoresistive element is used to thermally drive vibration in the
microcantilever.
Embodiment 28
The system of any one of Embodiments 1 through 8, wherein a
piezoresistive element is used to sense vibration in the
microcantilever.
Embodiment 29
The system of Embodiment 27 or Embodiment 28, wherein the
piezoresistive element is formed on a layer of single-crystal
silicon by depositing polycrystalline silicon with a dielectric
layer positioned between the single-crystal silicon layer and the
piezoresistive layer.
Embodiment 30
The system of Embodiment 27 or Embodiment 28, wherein the
piezoresistive element comprises a thin film metal layer.
Embodiment 31
The system of any one of Embodiments 1 through 8, wherein a
resistive heater is included on the surface of the microcantilever
for setting and sensing temperature of the microcantilever.
Embodiment 32
The system of any one of Embodiments 1 through 8, wherein the data
collected from all sensors is compared to a stored database of
fingerprints to detect, identify, and quantify the sampled gas.
Embodiment 33
The system of any one of Embodiments 1 through 8, wherein the gas
is concentrated prior to being exposed to the sensors.
Embodiment 34
The system of any one of Embodiments 1 through 8, wherein the gas
is passed through a separator prior to being exposed to the
sensors.
Embodiment 35
The system of Embodiment 34, wherein the gas transit time through
the separator varies by gas type.
Embodiment 36
The system of Embodiment 35, wherein the separator is a gas
chromatograph.
Embodiment 37
The system of Embodiment 35, wherein the gas is periodically
sampled over a time and correlated to the stored data base of
fingerprints and known gas transit times for the separator.
Embodiment 38
The system of any one of Embodiments 2 through 4 or 6 through 8,
wherein the temperature is ramped in predetermined temperature
steps on both the catalytic and catalytic reference microhotplates
and the power required to achieve each temperature step is
monitored by measuring the voltage and current to the resistive
heater on the microhotplate.
Embodiment 39
The system of Embodiment 38, wherein the power required to achieve
each temperature step of a previously measured baseline temperature
ramp is subtracted from the current temperature ramp to produce a
delta catalytic and delta catalytic reference signal.
Embodiment 40
The system of Embodiment 39, wherein the delta catalytic reference
signal is subtracted from the delta catalytic signal to produce a
measurement proportional to exothermic heat signal produced by the
catalytic sensor.
Embodiment 41
A method of detecting, identifying, and quantifying gases, the
method comprising: detecting the gas' thermal conductivity;
detecting the gas' viscous damping; compensating the thermal
conductivity and viscous damping for the effects of temperature,
pressure, and humidity; determining the slope and magnitude of the
thermal conductivity versus viscous damping vector relative to a
stored baseline; identifying the gas by the slope of the thermal
conductivity versus viscous damping vector; and quantifying the gas
by applying a stored gas specific calibration to the magnitude of
the thermal conductivity versus viscous damping vector.
Embodiment 42
A method of detecting, identifying, and quantifying gases, the
method comprising: detecting a gas' exothermic reaction and
light-off temperature(s); detecting the gas' thermal conductivity;
detecting the gas' viscous damping; compensating the thermal
conductivity and viscous damping for the effects of temperature,
pressure, and humidity; determining the slope and magnitude of the
thermal conductivity versus viscous damping vector relative to a
stored baseline; identifying the gas by the slope of the thermal
conductivity versus viscous damping vector and the light-off
temperature(s); and quantifying the gas by applying a stored gas
specific calibration to the magnitude of the thermal conductivity
versus viscous damping vector.
Embodiment 43
A method for detecting, identifying and quantifying gases, the
method comprising: detecting the gas' exothermic reaction and
light-off temperature(s); detecting the gas' thermal conductivity;
detecting the gas' viscous damping; collecting responses from a
plurality of MOS sensors; compensating the detected responses for
temperature, pressure, and humidity, parsing flammable from
non-flammable gases; identifying flammable gases by the light-off
temperature and the slope of thermal conductivity versus viscous
damping vector relative to a stored baseline; identifying
non-flammable gases by the slope of thermal conductivity versus
viscous damping vector relative to a stored baseline; utilizing the
MOS sensor responses to parse gas identification ambiguities and to
identify and quantify gases that are not detectable with a thermal
conductivity versus viscous damping vector; and quantifying gases
with detected changes to thermal conductivity and viscous damping
by applying a stored gas specific calibration to the magnitude of
the thermal conductivity versus viscous damping vector.
Embodiment 44
A method for detecting, identifying and quantifying gases, the
method comprising: detecting the gas' exothermic reaction and
light-off temperature(s); detecting the gas' thermal conductivity;
detecting the gas' viscous damping: collecting responses from a
plurality of MOS sensors; collecting responses from a plurality of
microcantilever sensors; compensating all the sensor responses for
temperature, pressure, and humidity, parsing flammable from
non-flammable gases; identifying flammable gases by the light-off
temperature and the slope of thermal conductivity versus viscous
damping vector relative to a stored baseline; identifying
non-flammable gases by the slope of thermal conductivity versus
viscous damping vector relative to a stored baseline; utilizing the
MOS sensor responses and coated microcantilever responses to parse
gas identification ambiguities and to identify and quantify gases
that are not detectable with a thermal conductivity versus viscous
damping vector; and quantifying gases with detected changes to
thermal conductivity and viscous damping by applying a stored gas
specific calibration to the magnitude of the thermal conductivity
versus viscous damping vector.
Embodiment 45
A method of detecting, identifying, and quantifying gases, the
method comprising: detecting the gas' thermal conductivity;
detecting the gas' viscous damping; compensating the thermal
conductivity and viscous damping for the effects of temperature,
pressure, and humidity; determining the slope and magnitude of the
thermal conductivity versus viscous damping vector relative to a
stored baseline; identifying the gas by the slope of the thermal
conductivity versus viscous damping vector; and quantifying the gas
by applying a stored gas specific calibration to the magnitude of
the thermal conductivity versus viscous damping vector.
Embodiment 46
A method of detecting, identifying, and quantifying gases, the
method comprising: detecting a gas' exothermic reaction and
light-off temperature(s); detecting the gas' thermal conductivity;
detecting the gas' viscous damping; compensating the thermal
conductivity and viscous damping for the effects of temperature,
pressure, and humidity; determining the slope and magnitude of the
thermal conductivity versus viscous damping vector relative to a
stored baseline; identifying the gas by the slope of the thermal
conductivity versus viscous damping vector and the light-off
temperature(s); and quantifying the gas by applying a stored gas
specific calibration to the magnitude of the thermal conductivity
versus viscous damping vector.
Embodiment 47
A method for detecting, identifying and quantifying gases, the
method comprising: detecting the gas' exothermic reaction and
light-off temperature(s); detecting the gas' thermal conductivity;
detecting the gas' viscous damping; collecting responses from a
plurality of MOS sensors; compensating the detected responses for
temperature, pressure, and humidity, parsing flammable from
non-flammable gases; identifying flammable gases by the light-off
temperature and the slope of thermal conductivity versus viscous
damping vector relative to a stored baseline; identifying
non-flammable gases by the slope of thermal conductivity versus
viscous damping vector relative to a stored baseline; utilizing the
MOS sensor responses to parse gas identification ambiguities and to
identify and quantify gases that are not detectable with a thermal
conductivity versus viscous damping vector; and quantifying gases
with detected changes to thermal conductivity and viscous damping
by applying a stored gas specific calibration to the magnitude of
the thermal conductivity versus viscous damping vector.
Embodiment 48
A method for detecting, identifying and quantifying gases, the
method comprising: detecting the gas' exothermic reaction and
light-off temperature(s); detecting the gas' thermal conductivity;
detecting the gas' viscous damping collecting responses from a
plurality of MOS sensors; collecting responses from a plurality of
microcantilever sensors; compensating all the sensor responses for
temperature, pressure, and humidity, parsing flammable from
non-flammable gases; identifying flammable gases by the light-off
temperature and the slope of thermal conductivity versus viscous
damping vector relative to a stored baseline; identifying
non-flammable gases by the slope of thermal conductivity versus
viscous damping vector relative to a stored baseline; utilizing the
MOS sensor responses and coated microcantilever responses to parse
gas identification ambiguities and to identify and quantify gases
that are not detectable with a thermal conductivity versus viscous
damping vector; and quantifying gases with detected changes to
thermal conductivity and viscous damping by applying a stored gas
specific calibration to the magnitude of the thermal conductivity
versus viscous damping vector.
Embodiment 49
The method of any one of Embodiments 41 through 48, that further
measures the thermal conductivity at multiple temperatures and
utilizes the resultant thermal conductivity versus temperature
vector as an additional measure of the gas concentration and
identification.
Embodiment 50
The method of any one of Embodiments 41 through 48, wherein the
gas' thermal conductivity is measured at a temperature greater than
an ambient temperature.
Embodiment 51
The method of any one of Embodiments 41 through 48, that parses
gases by those that are less dense than air and those that are
denser than air.
Embodiment 52
The method of any one of Embodiments 41 through 48, further
utilizing a temperature sensor that is used to compensate the
microhotplate and microcantilever sensor measurements for
temperature variations.
Embodiment 53
The method of any one of Embodiments 41 through 48, further
utilizing a humidity sensor that is used to compensate the
microhotplate and microcantilever sensor measurements for humidity
variations.
Embodiment 54
The method of any one of Embodiments 41 through 48, further
utilizing a pressure sensor that is used to compensate the
microhotplate and microcantilever sensor measurements for pressure
variations.
Embodiment 55
The method of any one of Embodiments 42 through 44 or 46 through
48, wherein the reference sensor response is subtracted from the
catalytic sensor response to compensate the catalytic sensor for
temperature, pressure, humidity and flow variations.
Embodiment 56
The method of any one of Embodiments 41 through 48, wherein a
baseline response from each of the sensors is stored prior to
detection of a gas and subsequently subtracted from each sensors'
response to produce a delta response that is used in further
analysis.
Embodiment 57
The method of any one of Embodiments 41 through 48, further
utilizing a filter that selectively restricts gas flow to the
microhotplates from the external gas environment.
Embodiment 58
The method of any one of Embodiments 41 through 48, further
utilizing a flame arrestor between the microhotplates and the
external gas environment.
Embodiment 59
The method of any one of Embodiments 41 through 48, wherein the
quality factor of the micro cantilever is derived and used to parse
the individual contributions of viscous damping components of
density and viscosity, wherein the combined analysis of density,
viscosity, and thermal conductivity are utilized to identify gas
component identification and its concentration.
Embodiment 60
The method of any one of Embodiments 42 through 44 or 46 through
48, wherein the measured responses from the microhotplate reference
sensor, the microhotplate catalytic sensor and the microcantilever
sensor responses are compared with each other to compensate for
sensor drift and to detect malfunctions.
Embodiment 61
The method of any one of Embodiments 41 through 48, wherein the
circuitry is operated at reduced power between measurements.
Embodiment 62
The method of any one of Embodiments 41 through 48, wherein
calibration data for the sensors is stored in a non-volatile memory
and used to calibrate the sensor measurements.
Embodiment 63
The method of any one of Embodiments 41 through 48, wherein the
calibration data for quantifying the gas concentration is stored in
non-volatile memory and selected based on the gas identity.
Embodiment 64
The method of any one of Embodiments 41 through 48, wherein sensor
response profiles for different gases are stored in a non-volatile
memory.
Embodiment 65
The method of any one of Embodiments 41 through 48, wherein a
microcantilever is used to sense viscous damping and a single
piezoelectric element is used to drive and detect the
microcantilever vibration.
Embodiment 66
The method of any one of Embodiments 41 through 48, wherein a
microcantilever is used to sense viscous damping and the
microcantilever vibration is driven with a piezoelectric element
and sensed with a piezoresistive element.
Embodiment 67
The method of any one of Embodiments 41 through 48, wherein a
microcantilever is used to sense viscous damping and a
piezoresistive element is used to thermally drive vibration in the
microcantilever.
Embodiment 68
The method of any one of Embodiments 41 through 48, wherein a
microcantilever is used to sense viscous damping and a
piezoresistive element is used to sense vibration in the
microcantilever.
Embodiment 69
The method of Embodiment 67 or Embodiment 68, wherein the
piezoresistive element is formed on a layer of single-crystal
silicon by depositing polycrystalline silicon with a dielectric
layer positioned between the single-crystal silicon layer and the
piezoresistive layer.
Embodiment 70
The method of Embodiment 67 or Embodiment 68, wherein the
piezoresistive element is formed by a thin film metal layer.
Embodiment 71
The method of any one of Embodiments 41 through 48, wherein the
data collected from all sensors is compared to a stored database of
fingerprints to detect, identify and quantify the sampled gas.
Embodiment 72
The method of any one of Embodiments 41 through 48, wherein the gas
is concentrated prior to being exposed to the sensors.
Embodiment 73
The method of any one of Embodiments 41 through 48, wherein the gas
is passed through a separator prior to being exposed to the
sensors.
Embodiment 74
The method of Embodiment 73, wherein the gas transit time through
the separator varies by gas type.
Embodiment 75
The method of Embodiment 73, wherein the separator is a gas
chromatograph.
Embodiment 76
The method of Embodiment 73, wherein the gas is periodically
sampled over a time and correlated to the stored data base of
fingerprints and known gas transit times for the separator.
Embodiment 77
The method of any one of Embodiments 42 through 44 or 46 through
48, wherein the temperature is ramped in predetermined temperature
steps on both the catalytic and catalytic reference microhotplates
and the power required to achieve each temperature step is
monitored by measuring the voltage and current to the resistive
heater on the microhotplate.
Embodiment 78
The method of Embodiment 77, wherein the power required to achieve
each temperature step of a previously measured baseline temperature
ramp is subtracted from the current temperature ramp to produce a
delta catalytic and delta catalytic reference signal.
Embodiment 79
The method of Embodiment 78, wherein the delta catalytic reference
signal is subtracted from the delta catalytic signal to produce a
measurement proportional to exothermic heat signal produced by the
catalytic sensor.
Embodiment 80
A system for determining one or more properties of one or more
samples, the system comprising: a thermal conductivity sensor
configured to measure a response of the thermal conductivity sensor
to exposure to a sample at two or more temperatures; and a
processing subsystem configured to: determine a thermal
conductivity of the sample at each of the two or more temperatures
responsive to an output of the thermal conductivity sensor; and
determine a presence of at least one component of the sample based
at least in part on the thermal conductivity of the sample at each
of the two or more temperatures.
Embodiment 81
The system of Embodiment 80, wherein the processing subsystem is
configured to determine the thermal conductivity of the sample at
each of the two or more temperatures by subtracting a baseline
response of the thermal conductivity sensor from a response of the
thermal conductivity sensor at each of the two or more respective
temperatures to exposure to the sample.
Embodiment 82
The system of Embodiment 80 or Embodiment 81, wherein the
processing subsystem is configured to determine an identity of the
sample based on a ratio of the thermal conductivity of the sample
at a first temperature of the two or more temperatures to the
thermal conductivity of the sample at a second temperature of the
two or more temperatures.
Embodiment 83
The system of any one of Embodiments 80 through 82, wherein the
processing subsystem is further configured to determine a
concentration of the sample based on at least one of the thermal
conductivity of the sample at a first temperature and the thermal
conductivity of the sample at a second temperature.
Embodiment 84
The system of any one of Embodiments 80 through 83, further
comprising a catalytic microhotplate sensor, wherein the processing
subsystem is further configured receive an output of the catalytic
microhotplate sensor responsive to exposing the catalytic
microhotplate sensor to the sample at each of the two or more
temperatures.
Embodiment 85
The system of Embodiment 84, wherein the catalytic microhotplate
sensor is located to be exposed to the sample at each of the two or
more temperatures at the same time as the thermal conductivity
sensor is exposed to the sample at each of the two or more
temperatures.
Embodiment 86
The system of Embodiment 84 or Embodiment 85, wherein the
processing subsystem is configured to determine a ratio of the
output of the catalytic microhotplate sensor at a first temperature
to exposure to the sample at the first temperature to the output of
the catalytic microhotplate sensor at a second temperature to
exposure to the sample at the second temperature.
Embodiment 87
The system of any one of Embodiments 84 through 86, wherein the
processing subsystem is configured to compensate the output of the
catalytic microhotplate sensor based on the output of the thermal
conductivity sensor.
Embodiment 88
The system of any one of Embodiments 84 through 87, wherein the
processing subsystem is configured to determine a temperature of
one of an exothermic reaction and a reaction onset based on the
output of the catalytic microhotplate sensor.
Embodiment 89
The system of any one of Embodiments 84 through 88, wherein the
processing subsystem is further configured to determine a
concentration of the at least one component of the sample based on
at least one of a magnitude of the output of the catalytic
microhotplate sensor and a magnitude of the output of the thermal
conductivity sensor at one or more of the two more
temperatures.
Embodiment 90
The system of any one of Embodiments 84 through 89, further
comprising a microcantilever sensor configured to be exposed to the
gas sample, wherein the processing subsystem is configured to
determine at least one property of the microcantilever sensor, the
at least one property of the microcantilever sensor selected from
the group consisting of a quality factor, a resonant frequency, a
series capacitance, a series inductance, a series resistance, a
viscous damping and a bandwidth of the microcantilever sensor,
wherein the processing subsystem is configured to determine the
presence of the at least one component of the sample based, at
least in part, on the at least one property of the microcantilever
sensor.
Embodiment 91
The system of Embodiment 90, wherein the processing subsystem is
configured to determine a concentration of the at least one
component of the sample based on a viscous damping of the sample
and the thermal conductivity of the sample at one or more of the
two or more temperatures.
Embodiment 92
The system of any one of Embodiments 80 through 91, further
comprising at least one of a coated microcantilever sensor and a
metal oxide semiconductor sensor configured to interact with one or
more specific analytes present in the sample.
Embodiment 93
A system for determining at least one property of a sample, the
system comprising: an inert microcantilever located to be exposed
to a sample comprising an analyte of interest; and a processing
subsystem comprising: a memory including baseline data comprising a
resonant frequency of the inert microcantilever and at least one of
a quality factor and a series resistance of the inert
microcantilever responsive to exposure to a reference sample; and a
processor configured to determine a presence of the analyte of
interest based, at least in part, on a change in resonant frequency
and at least one of a change in quality factor and series
resistance of the inert microcantilever responsive to exposure to
the sample.
Embodiment 94
The system of Embodiment 93, further comprising a thermal
conductivity sensor, wherein the processing subsystem is further
configured to determine the presence of the analyte of interest
based on a thermal conductivity of the sample at one or more
temperatures.
Embodiment 95
The system of Embodiment 93 or Embodiment 94, wherein the
processing subsystem is configured to determine a concentration of
the analyte of interest based on at least one of a magnitude of the
change in resonant frequency, a magnitude of the change in quality
factor, and a magnitude of the change in series resistance of the
inert microcantilever responsive to exposure to the sample.
Embodiment 96
A method of determining at least one property of a sample, the
method comprising: exposing a thermal conductivity sensor of a
detector to a sample; determining a thermal conductivity of the
sample at a first temperature and at a second temperature; and
determining a presence of one or more analytes in the sample based,
at least in part, on a ratio of the thermal conductivity of the
sample at the first temperature to the thermal conductivity of the
sample at the second temperature.
Embodiment 97
The method of Embodiment 96, further comprising selecting the first
temperature to be between about 50.degree. C. and about 250.degree.
C. and selecting the second temperature to be between about
300.degree. C. and about 800.degree. C.
Embodiment 98
The method of Embodiment 96 or Embodiment 97, further comprising
determining a concentration of the one or more analytes based on
the thermal conductivity of the sample at the first temperature and
the thermal conductivity of the sample at the second
temperature.
Embodiment 99
The method of any one of Embodiments 96 through 98, further
comprising selecting the first temperature and the second
temperature to be greater than a boiling point of water at a
selected atmospheric pressure.
Embodiment 100
The method of any one of Embodiments 96 through 99, further
comprising selecting at least one of the first temperature and the
second temperature to be a temperature at which a thermal
conductivity of air is substantially the same as a thermal
conductivity of water.
Embodiment 101
The method of any one of Embodiments 96 through 100, further
comprising exposing a catalytic microhotplate sensor to the sample
at the first temperature and the second temperature and measuring a
response of the catalytic microhotplate sensor at each of the first
temperature and the second temperature to exposure to the
sample.
Embodiment 102
The method of Embodiment 101, wherein determining a presence of one
or more analytes further comprises determining the presence of the
one or more analytes based on a ratio of the response of the
catalytic microhotplate sensor at the first temperature to the
response of the catalytic microhotplate sensor at the second
temperature.
Embodiment 103
The method of Embodiment 101 or Embodiment 102, wherein determining
a presence of one or more analytes further comprises determining
the presence of the one or more analytes based on a ratio of the
response of the catalytic microhotplate sensor at one or more
temperatures to a response of the thermal conductivity sensor at
the one or more temperatures.
Embodiment 104
The method of any one of Embodiments 96 through 103, further
comprising determining a resonant frequency and at least one of a
quality factor and a series resistance of an inert microcantilever
exposed to the sample.
Embodiment 105
The method of Embodiment 104, wherein determining a presence of one
or more analytes in the sample further comprises determining a
presence of one or more analytes in the sample based on a ratio of
the resonant frequency to the at least one of a quality factor and
a series resistance of the inert microcantilever.
Embodiment 106
The method of any one of Embodiments 96 through 105, further
comprising measuring a response of at least one of a metal oxide
semiconductor sensor and a coated microcantilever to exposure to
the sample.
Embodiment 107
The method of Embodiment 106, wherein determining a presence of one
or more analytes in the sample further comprises determining a
presence of one or more analytes in the sample based, at least in
part, on a resistance of the metal oxide semiconductor sensor
responsive to exposure to the sample.
Embodiment 108
A gas analysis system, comprising: at least one sensor; a
processing subsystem in operable communication with the at least
one sensor, the processing subsystem configured to create one or
more vectors based on two or more sensor parameters of a set of
sensor parameters, the set of sensor parameters including: a
thermal conductivity of a sample at a first temperature; a thermal
conductivity of the sample at a second temperature; an exothermic
response at the first temperature; an exothermic response at the
second temperature; a resonant frequency shift of a microcantilever
responsive to exposure to the sample; a qualify factor shift of the
microcantilever responsive to exposure to the sample; at least one
equivalent circuit parameter shift of the microcantilever
responsive to exposure to the sample; a metal oxide semiconductor
resistance shift at the first temperature responsive to exposure to
the sample; a metal oxide semiconductor resistance shift at the
second temperature responsive to exposure to the sample; wherein
the processing subsystem is further configured to: compensate a
response of the at least one sensor for effects of one or more of
temperature, pressure, and humidity; determine an identity of one
or more gases in the sample based on a direction of the one or more
vectors; and determine a concentration of the one or more gases in
the sample based on a magnitude of the one or more vectors.
Embodiment 109
The gas analysis system of Embodiment 108, wherein the processing
subsystem is configured to determine an identity and concentration
of one or more gases in the sample based on a multi-dimensional
vector formed from three or more sensor parameters of the set of
sensor parameters.
Embodiment 110
The gas analysis system of Embodiment 108 or Embodiment 109,
wherein the processing subsystem is configured to determine an
identity of one or more gases in the sample based on a relationship
between at least two sensor parameters of the set of sensor
parameters with each of at least two other of the sensor parameters
of the set of sensor parameters.
Embodiment 111
The gas analysis system of any one of Embodiments 108 through 110,
wherein the processing subsystem is configured to determine an
identity of one or more gases in the sample based on a relationship
between the thermal conductivity of the sample at the first
temperature, the thermal conductivity of the sample at the second
temperature, the exothermic response at the first temperature, and
the exothermic response at the second temperature.
Embodiment 112
The gas analysis system of any one of Embodiments 108 through 111,
wherein the processing subsystem is further configured to determine
an identity of one or more gases in the sample based on the
resonant frequency shift of the microcantilever responsive to
exposure to the sample and the at least one equivalent circuit
parameter shift of the microcantilever responsive to exposure to
the sample.
Embodiment 113
A system for determining one or more properties of one or more
samples, the system comprising: at least one thermal conductivity
sensor configured to measure a response of the at least one thermal
conductivity sensor to exposure to a sample while the at least one
thermal conductivity sensor is at a first temperature and while the
at least one thermal conductivity sensor is at at least a second
temperature; and a subsystem configured to determine a presence of
at least one component of the sample based, at least in part, on
the response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at the first temperature and the response of the at least
one thermal conductivity sensor to exposure to the sample while the
at least one thermal conductivity sensor is at the at least a
second temperature.
Embodiment 114
The system of Embodiment 113, wherein the subsystem is configured
to: determine a first difference between the response of the at
least one thermal conductivity sensor to exposure to the sample
while the at least one thermal conductivity sensor is at the first
temperature and a baseline response of the at least one thermal
conductivity sensor while the at least one thermal conductivity
sensor is at the first temperature; and determine a second
difference between the response of the at least one thermal
conductivity sensor to exposure to the sample while the at least
one thermal conductivity sensor is at the at least a second
temperature and a baseline response of the at least one thermal
conductivity sensor while the at least one thermal conductivity
sensor is at the at least a second temperature.
Embodiment 115
The system of Embodiment 114, wherein the subsystem is configured
to determine an identity of the sample based on a ratio of the
first difference to the second difference.
Embodiment 116
The system of Embodiment 114, wherein the subsystem is configured
to determine a concentration of the sample based on at least one of
a magnitude of a combined vector of the first difference, the
second difference, a magnitude of the first difference, and a
magnitude of the second difference.
Embodiment 117
The system of any one of Embodiments 114 through 116, wherein the
baseline response while the at least one thermal conductivity
sensor is at the first temperature and at the at least a second
temperature comprises a response of the at least one thermal
conductivity sensor to exposure to air while the at least one
thermal conductivity sensor is at each of the respective first
temperature and the at least a second temperature.
Embodiment 118
The system of any one of Embodiments 114 through 116, wherein the
baseline response while the at least one thermal conductivity
sensor is at the first temperature and the at least a second
temperature comprises a response of the at least one thermal
conductivity sensor to exposure to a reference gas while the at
least one thermal conductivity sensor is at each of the respective
first temperature and the at least a second temperature.
Embodiment 119
The system of Embodiment 118, wherein the subsystem is configured
to: determine a difference between the thermal conductivity of the
sample and the thermal conductivity of the reference gas while the
at least one thermal conductivity sensor is at the first
temperature; and determine a difference between the thermal
conductivity of the sample and the thermal conductivity of the
reference gas while the at least one thermal conductivity sensor is
at the at least a second temperature.
Embodiment 120
The system of any one of Embodiments 113 through 119, wherein the
at least one thermal conductivity sensor comprises a first thermal
conductivity sensor configured to be exposed to the sample while
the first thermal conductivity sensor is at the first temperature
and a second thermal conductivity sensor configured to be exposed
to the sample while the second thermal conductivity sensor is at
the at least a second temperature.
Embodiment 121
The system of any one of Embodiments 113 through 119, wherein the
at least one thermal conductivity sensor comprises a single thermal
conductivity sensor configured to be exposed to the sample while
the single thermal conductivity sensor is at the first temperature
and the at least a second temperature.
Embodiment 122
The system of any one of Embodiments 113 through 121, further
comprising a controller configured to ramp a temperature of the at
least one thermal conductivity sensor to a predetermined
temperature while the at least one thermal conductivity sensor is
exposed to the sample.
Embodiment 123
The system of any one of Embodiments 113 through 122, wherein the
subsystem is configured to determine an identity of the sample
based on a ratio of the response of the at least one thermal
conductivity sensor to exposure to the sample while the at least
one thermal conductivity sensor is at the first temperature to the
response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at the at least a second temperature.
Embodiment 124
The system of any one of Embodiments 113 through 123, wherein the
subsystem is further configured to determine at least one of an
average molecular weight and a concentration of the sample, based
on a relationship between a concentration of the sample and the
response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at the first temperature or while the at least one
thermal conductivity sensor is at the at least a second
temperature.
Embodiment 125
The system of any one of Embodiments 113 through 124, wherein the
subsystem is configured to determine an identity of the sample
based on a temperature at which a thermal conductivity of the
sample is equal to a thermal conductivity of air.
Embodiment 126
The system of any one of Embodiments 113 through 125, wherein the
subsystem is further configured to determine a thermal conductivity
of the sample at a temperature at which a thermal conductivity of
air is equal to a thermal conductivity of humid air.
Embodiment 127
The system of any one of Embodiments 113 through 126, wherein the
subsystem is further configured to determine a concentration of the
sample based on at least one of a magnitude of a vector of the
response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at the first temperature versus the response of the at
least one thermal conductivity sensor to exposure to the sample
while the at least one thermal conductivity sensor is at the at
least a second temperature and a magnitude of the response of the
at least one thermal conductivity sensor to exposure to the sample
while the at least one thermal conductivity sensor is at one or
both of the first temperature and the at least a second
temperature.
Embodiment 128
The system of any one of Embodiments 113 through 127, further
comprising at least one environmental sensor configured to measure
at least one of a temperature, a pressure, a humidity, and a
flowrate, wherein the subsystem is further configured to compensate
an output of the at least one thermal conductivity sensor for the
at least one of temperature, pressure, humidity, and flowrate.
Embodiment 129
The system of any one of Embodiments 113 through 128, wherein the
subsystem is configured to determine the response of the at least
one thermal conductivity sensor to exposure to the sample while the
at least one thermal conductivity sensor is at a first temperature
between about 50.degree. C. and about 250.degree. C. and the
response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at a second temperature between about 300.degree. C. and
about 800.degree. C.
Embodiment 130
The system of any one of Embodiments 113 through 129, further
comprising a catalytic sensor, wherein the subsystem is configured
to determine the presence of the at least one component based on a
difference between a response of the catalytic sensor to exposure
to the sample while the catalytic sensor is at one of the first
temperature and the at least a second temperature and the response
of the at least one thermal conductivity sensor to exposure to the
sample while the at least one thermal conductivity sensor is at the
respective one of the first temperature and the at least a second
temperature.
Embodiment 131
The system of any one of Embodiments 113 through 130, further
comprising a damping sensor, wherein the subsystem is further
configured to determine a presence of the at least one component
based on a relationship between a response of the damping sensor to
exposure to the sample relative to a baseline response of the
damping sensor to exposure to a reference gas.
Embodiment 132
The system of Embodiment 131, wherein the subsystem is configured
to determine the presence of the at least one component based on a
relationship between a change in at least one resonant parameter of
the damping sensor relative to a baseline of the at least one
resonant parameter.
Embodiment 133
The system of Embodiment 130 or Embodiment 131, wherein the damping
sensor comprises a microcantilever.
Embodiment 134
The system of any one of Embodiments 113 through 133, further
comprising a metal oxide semiconductor sensor configured to
interact with one or more specific analytes in the sample, wherein
the subsystem is further configured to determine the presence of
the at least one component of the sample based on a response of the
metal oxide semiconductor sensor to exposure to the sample.
Embodiment 135
The system of any one of Embodiments 113 through 134, further
comprising a microcantilever sensor comprising a coating formulated
to interact with one or more specific analytes present in the
sample, wherein the subsystem is further configured to determine
the presence of the at least one component of the sample based on
one or more resonant parameters of the microcantilever sensor
responsive to exposure to the sample.
Embodiment 136
A system for determining at least one property of a sample, the
system comprising: at least one thermal conductivity sensor; at
least one damping sensor; and a subsystem configured to: while the
at least one thermal conductivity sensor is at a temperature
greater than about 50.degree. C., determine a response of the at
least one thermal conductivity sensor to exposure to a sample;
determine a response of the at least one damping sensor to exposure
to the sample; and determine a presence of at least one component
of the sample based, at least in part, on a relationship between
the response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at the temperature greater than about 50.degree. C. and
the response of the damping sensor to exposure to the sample.
Embodiment 137
The system of Embodiment 136, wherein the subsystem is configured
to: determine a response of the at least one thermal conductivity
sensor to exposure to the sample relative to a baseline response of
the at least one thermal conductivity sensor; and determine a
response of the at least one damping sensor to exposure to the
sample relative to a baseline response of the at least one damping
sensor.
Embodiment 138
The system of Embodiment 136, wherein the subsystem is configured
to: determine a change in thermal conductivity of the sample
relative to a reference gas based on a difference between the
thermal conductivity of the sample and the thermal conductivity of
the reference gas; and determine a change in at least one resonant
parameter of the at least one damping sensor based on a difference
between the response of the at least one damping sensor to exposure
to the sample and the baseline response of the at least one damping
sensor.
Embodiment 139
The system of Embodiment 138, wherein the subsystem is configured
to determine an identity of the sample based on a ratio of the
difference between the thermal conductivity of the sample and the
thermal conductivity of the reference gas and the difference
between the response of the at least one damping sensor to exposure
to the sample and the baseline response of the at least one damping
sensor.
Embodiment 140
The system of Embodiment 138 or Embodiment 139, wherein the
subsystem is configured to determine a concentration of the sample
based on a magnitude of a vector of the change in the thermal
conductivity versus the change in the at least one resonant
parameter.
Embodiment 141
The system of any one of Embodiments 138 through 140, wherein the
subsystem is configured to determine a presence of the at least one
component of the sample based on a relationship between the change
in the thermal conductivity of the sample relative to the reference
gas, the change in the at least one resonant parameter of the at
least one damping sensor, and a change in at least another resonant
parameter of the at least one damping sensor.
Embodiment 142
The system of any one of Embodiments 136 through 141, wherein the
at least one damping sensor comprises a microcantilever.
Embodiment 143
The system of any one of Embodiments 136 through 142, further
comprising a controller configured to ramp a temperature of the at
least one thermal conductivity sensor to a predetermined
temperature while the at least one thermal conductivity sensor is
exposed to the sample.
Embodiment 144
The system of any one of Embodiments 136 through 143, further
comprising at least one environmental sensor configured to measure
at least one of a temperature, a pressure, a humidity, and a
flowrate, wherein the subsystem is further configured to compensate
the output of the at least one thermal conductivity sensor and an
output of the at least one damping sensor for the at least one of
temperature, pressure, humidity, and flowrate.
Embodiment 145
The system of any one of Embodiments 136 through 144, further
comprising a catalytic sensor, wherein the subsystem is further
configured to receive an output from the catalytic sensor
responsive to exposing the catalytic sensor to the sample and
further configured to determine the presence of the at least one
component based on the output of the catalytic sensor.
Embodiment 146
The system of Embodiment 145, wherein the catalytic sensor
comprises one of a catalytic microhotplate sensor and a catalytic
microcantilever sensor.
Embodiment 147
The system of Embodiment 145 or Embodiment 146, wherein the
subsystem is configured to determine at least one of an identity
and a concentration of at least one component of the sample based,
at least in part, on a relationship between the response of the at
least one thermal conductivity sensor to exposure to the sample and
the response of the at least one damping sensor to exposure to the
sample responsive to detecting an exothermic response from the
catalytic sensor.
Embodiment 148
The system of any one of Embodiments 136 through 147, further
comprising a metal oxide semiconductor sensor configured to
interact with one or more specific analytes present in the sample,
wherein the subsystem is further configured to determine the
presence of the at least one component of the sample based on a
response of the metal oxide semiconductor sensor to exposure to the
sample.
Embodiment 149
The system of any one of Embodiments 136 through 148, further
comprising a microcantilever sensor comprising a coating formulated
to interact with one or more specific analytes present in the
sample, wherein the subsystem is further configured to determine
the presence of the at least one component of the sample based on
one or more resonant parameters of the microcantilever sensor
responsive to exposure to the sample.
Embodiment 150
A system for determining at least one property of a sample, the
system comprising: at least one thermal conductivity sensor; at
least one catalytic sensor; and a subsystem configured to:
determine a response of the at least one thermal conductivity
sensor to exposure to the sample while the at least one thermal
conductivity sensor is at each of the first temperature and the at
least a second temperature; determine a response of the at least
one catalytic sensor to exposure to the sample while the at least
one catalytic sensor is at each of the first temperature and the at
least a second temperature; and determine a presence of at least
one component of the sample based, at least in part, on the
response of the at least one thermal conductivity sensor to
exposure to the sample while the at least one thermal conductivity
sensor is at each of the first temperature and the at least a
second temperature and the response of the at least one catalytic
sensor to exposure to the sample while the at least one catalytic
sensor is at each of the first temperature and the at least a
second temperature.
Embodiment 151
The system of Embodiment 150, wherein the subsystem is configured
to determine a change in the response of the at least one thermal
conductivity sensor to exposure to the sample while the at least
one thermal conductivity sensor is at each of the first temperature
and the at least a second temperature relative to a baseline
thermal conductivity response at each of the first temperature and
the at least a second temperature; determine a catalytic activity
at each of the first temperature and the at least a second
temperature by determining a change in the response of the at least
one catalytic sensor to exposure to the sample while the at least
one catalytic sensor is at each of the first temperature and the at
least a second temperature relative to a baseline catalytic
response at each of the respective first temperature and the at
least a second temperature; and determine the presence of the at
least one component based on: the change in the response of the at
least one thermal conductivity sensor to exposure to the sample
while the at least one thermal conductivity sensor is at each of
the first temperature and the at least a second temperature; and
the catalytic activity at the first temperature and the catalytic
activity at the at least a second temperature.
Embodiment 152
The system of Embodiment 151, wherein the subsystem is configured
to determine the presence of the at least one component based on:
an exothermic response at the first temperature determined by a
difference between the catalytic activity at the first temperature
and the change in the response of the at least one thermal
conductivity sensor at the first temperature; and an exothermic
response at the at least a second temperature determined by a
difference between the catalytic activity at the at least a second
temperature and the change in the response of the at least one
thermal conductivity sensor at the at least a second
temperature.
Embodiment 153
The system of Embodiment 152, wherein the subsystem is configured
to determine the presence of the at least one component based on a
ratio of the exothermic response at the first temperature to the
exothermic response at the at least a second temperature.
Embodiment 154
The system of any one of Embodiments 151 through 153, wherein the
subsystem is configured to determine an identity of the at least
one component of the sample responsive to determining a temperature
at which a change in the response of the at least one thermal
conductivity sensor and a catalytic activity of the at least one
catalytic sensor to exposure to the sample is greater than a
threshold value.
Embodiment 155
The system of any one of Embodiments 151 through 154, wherein the
subsystem is further configured to determine an identity of the
sample based on a ratio of the catalytic activity at the first
temperature to the catalytic activity at the at least a second
temperature.
Embodiment 156
The system of any one of Embodiments 151 through 155, wherein the
subsystem is further configured to determine a concentration of one
or more gases in the sample based on at least one of a magnitude of
the catalytic activity at the first temperature and the magnitude
of the catalytic activity at the at least a second temperature.
Embodiment 157
The system of any one of Embodiments 151 through 156, wherein the
subsystem is configured to determine an identity of the sample
based on a ratio of at least two of: the change in the response of
the at least one thermal conductivity sensor to exposure to the
sample while the at least one thermal conductivity sensor is at the
first temperature; the change in the response of the at least one
thermal conductivity sensor to exposure to the sample while the at
least one thermal conductivity sensor is at the at least a second
temperature; the catalytic activity at the first temperature; and
the catalytic activity at the at least a second temperature.
Embodiment 158
The system of any one of Embodiments 151 through 157, wherein the
subsystem is configured to determine a concentration of at least
one component of the sample based on at least one of: a magnitude
of the change in the response of the at least one thermal
conductivity sensor to exposure to the sample while the at least
one thermal conductivity sensor is at the first temperature; a
magnitude of the change in the response of the at least one thermal
conductivity sensor to exposure to the sample while the at least
one thermal conductivity sensor is at the at least a second
temperature; a magnitude of the catalytic activity at the first
temperature; and a magnitude of the catalytic activity at the at
least a second temperature.
Embodiment 159
The system of any one of Embodiments 150 through 158, wherein the
catalytic sensor comprises a catalytic microhotplate sensor.
Embodiment 160
The system of any one of Embodiments 150 through 158, wherein the
catalytic sensor comprises a microcantilever sensor comprising a
heater.
Embodiment 161
The system of any one of Embodiments 150 through 160, further
comprising a damping sensor, wherein the subsystem is further
configured to determine an identity of at least one component of
the sample based on a change in at least one resonant parameter of
the damping sensor responsive to exposure to the sample relative to
a baseline value of the at least one resonant parameter.
Embodiment 162
The system of any one of Embodiments 150 through 161, further
comprising at least one environmental sensor configured to measure
at least one of a temperature, a pressure, a humidity, and a
flowrate, wherein the subsystem is further configured to compensate
the response of the at least one thermal conductivity sensor and an
output of the at least one catalytic sensor based on the measured
at least one of the temperature, the pressure, the humidity, and
the flowrate.
Embodiment 163
The system of any one of Embodiments 150 through 162, further
comprising a metal oxide semiconductor sensor configured to
interact with one or more specific analytes present in the sample,
wherein the subsystem is further configured to determine the
presence of at least one component of the sample based on a
response of the metal oxide semiconductor sensor to exposure to the
sample.
Embodiment 164
The system of any one of Embodiments 150 through 163, further
comprising at least one microcantilever sensor comprising a coating
formulated to interact with one or more specific analytes present
in the sample, wherein the subsystem is further configured to
determine the presence of at least one component of the sample
based on one or more resonant parameters of the at least one
microcantilever sensor responsive to exposure to the sample.
Embodiment 165
A system for determining an identity of a sample, the system
comprising: at least one thermal conductivity sensor; at least one
catalytic sensor; at least one damping sensor; and a subsystem
configured to: determine a thermal conductivity of the sample while
the at least one thermal conductivity sensor is at each of a first
temperature and at a second temperature based on a response of the
at least one thermal conductivity sensor to exposure to the sample
while the at least one thermal conductivity sensor is at the first
temperature and the second temperature; determine a response of the
at least one catalytic sensor to exposure to the sample while the
at least one catalytic sensor is at each of the first temperature
at the second temperature; determine a catalytic activity at each
of the first temperature and the second temperature by determining
a change in the response of the at least one catalytic sensor to
exposure to the sample while the at least one catalytic sensor is
at each of the first temperature and the second temperature
relative to a baseline catalytic response at each of the respective
first temperature and the second temperature; and determine a
response of the at least one damping sensor to exposure to the
sample.
Embodiment 166
The system of Embodiment 165, wherein the subsystem is configured
to determine a presence of at least one component of the sample
based on: an exothermic response at the first temperature
determined by a difference between the catalytic activity at the
first temperature and a change in the response of the at least one
thermal conductivity sensor to exposure to the sample at the first
temperature relative to a baseline thermal conductivity response of
the at least one thermal conductivity sensor at the first
temperature; and an exothermic response at the second temperature
determined by a difference between the catalytic activity at the
second temperature and a change in the response of the at least one
thermal conductivity sensor to exposure to the sample at the second
temperature relative to a baseline thermal conductivity response of
the at least one thermal conductivity sensor at the second
temperature.
Embodiment 167
The system of Embodiment 165 or Embodiment 166, wherein the
subsystem is configured to determine a presence of one or more
analytes in the sample based on a multi-dimensional analysis of: a
change in the thermal conductivity of the sample while the at least
one thermal conductivity sensor is at the first temperature
relative to a thermal conductivity of a reference gas while the at
least one thermal conductivity sensor is at the first temperature;
a change in the thermal conductivity of the sample while the at
least one thermal conductivity sensor is at the second temperature
relative to a thermal conductivity of the reference gas while the
at least one thermal conductivity sensor is at the second
temperature; the catalytic activity of the at least one catalytic
sensor at the first temperature; the at least one catalytic
activity of the at least one catalytic sensor at the second
temperature; and a change in at least one resonant parameter of the
at least one damping sensor relative to one or both of the change
in the thermal conductivity and the catalytic activity of the at
least one catalytic sensor at one or both of the first temperature
and the second temperature.
Embodiment 168
The system of any one of Embodiments 165 through 167, further
comprising a metal oxide semiconductor sensor configured to
interact with one or more specific analytes present in the sample,
wherein the subsystem is further configured to determine the
presence of at least one component of the sample based on a
response of the metal oxide semiconductor sensor to exposure to the
sample.
Embodiment 169
The system of any one of Embodiments 165 through 168, further
comprising at least one microcantilever sensor comprising a coating
formulated to interact with one or more specific analytes present
in the sample, wherein the subsystem is further configured to
determine the presence of at least one component of the sample
based on one or more resonant parameters of the at least one
microcantilever sensor responsive to exposure to the sample.
Embodiment 170
The system of any one of Embodiments 165 through 169, further
comprising a gas pre-concentrator positioned to be exposed to the
sample before the at least one thermal conductivity sensor, the at
least one catalytic sensor, and the at least one damping sensor,
wherein desorption of analytes from the gas pre-concentrator is
controlled by ramping a temperature of the gas pre-concentrator,
wherein the subsystem is configured to determine an identity of
different components based on at least one fingerprint produced at
at least one temperature.
Embodiment 171
The system of Embodiment 170, further comprising at least one of a
metal oxide semiconductor sensor and a coated microcantilever
sensor located proximate the gas pre-concentrator.
Embodiment 172
The system of any one of Embodiments 165 through 171, further
comprising a separator located proximate the at least one thermal
conductivity sensor, the at least one catalytic sensor, and the at
least one damping sensor, wherein the subsystem is configured to
determine an identity of different components in the sample based
on at least one fingerprint of each component during a time
sequenced output from the separator.
Embodiment 173
The system of Embodiment 172, further comprising at least one of a
metal oxide semiconductor sensor and coated microcantilever sensor
located proximate the gas separator.
While the embodiments of the invention disclosed herein are
presently considered to be preferred, various changes and
modifications can be made without departing from the spirit and
scope of the invention. The scope of the invention is indicated in
the appended claims, and all changes that come within the meaning
and range of equivalents are embraced herein.
While embodiments of the disclosure may be susceptible to various
modifications and alternative forms, specific embodiments have been
shown by way of example in the drawings and have been described in
detail herein. However, it should be understood that the disclosure
is not limited to the particular forms disclosed. Rather, the
disclosure encompasses all modifications, variations, combinations,
and alternatives falling within the scope of the disclosure as
defined by the following appended claims and their legal
equivalents.
* * * * *